From: Srikanth Yalavarthi <syalavarthi@marvell.com>
To: Srikanth Yalavarthi <syalavarthi@marvell.com>
Cc: <dev@dpdk.org>, <sshankarnara@marvell.com>, <aprabhu@marvell.com>,
<ptakkar@marvell.com>
Subject: [PATCH v3 15/35] ml/cnxk: update device and model xstats functions
Date: Wed, 27 Sep 2023 11:30:28 -0700 [thread overview]
Message-ID: <20230927183052.17347-16-syalavarthi@marvell.com> (raw)
In-Reply-To: <20230927183052.17347-1-syalavarthi@marvell.com>
Added cnxk wrapper function to handle ML device and model
extended stats. Handling resources for the xstats is done
in the cnxk layer. Introduced internal xstats group.
Signed-off-by: Srikanth Yalavarthi <syalavarthi@marvell.com>
---
drivers/ml/cnxk/cn10k_ml_dev.h | 4 -
drivers/ml/cnxk/cn10k_ml_ops.c | 531 +++----------------------------
drivers/ml/cnxk/cn10k_ml_ops.h | 16 +-
drivers/ml/cnxk/cnxk_ml_dev.h | 5 +
drivers/ml/cnxk/cnxk_ml_ops.c | 481 +++++++++++++++++++++++++++-
drivers/ml/cnxk/cnxk_ml_xstats.h | 21 +-
6 files changed, 551 insertions(+), 507 deletions(-)
diff --git a/drivers/ml/cnxk/cn10k_ml_dev.h b/drivers/ml/cnxk/cn10k_ml_dev.h
index be989e0a20..bde9d08901 100644
--- a/drivers/ml/cnxk/cn10k_ml_dev.h
+++ b/drivers/ml/cnxk/cn10k_ml_dev.h
@@ -10,7 +10,6 @@
#include "cn10k_ml_ocm.h"
#include "cnxk_ml_io.h"
-#include "cnxk_ml_xstats.h"
/* Dummy Device ops */
extern struct rte_ml_dev_ops ml_dev_dummy_ops;
@@ -133,9 +132,6 @@ struct cn10k_ml_dev {
/* OCM info */
struct cn10k_ml_ocm ocm;
- /* Extended stats data */
- struct cnxk_ml_xstats xstats;
-
/* Enable / disable model data caching */
int cache_model_data;
diff --git a/drivers/ml/cnxk/cn10k_ml_ops.c b/drivers/ml/cnxk/cn10k_ml_ops.c
index 27d255a830..776ad60401 100644
--- a/drivers/ml/cnxk/cn10k_ml_ops.c
+++ b/drivers/ml/cnxk/cn10k_ml_ops.c
@@ -198,107 +198,21 @@ cn10k_ml_prep_fp_job_descriptor(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_r
req->cn10k_req.jd.model_run.num_batches = op->nb_batches;
}
-static int
-cn10k_ml_xstats_init(struct rte_ml_dev *dev)
-{
- struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_dev *cnxk_mldev;
- uint16_t nb_stats;
- uint16_t stat_id;
- uint16_t model;
- uint16_t i;
-
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
-
- /* Allocate memory for xstats entries. Don't allocate during reconfigure */
- nb_stats = RTE_DIM(device_xstats) + ML_CNXK_MAX_MODELS * RTE_DIM(layer_xstats);
- if (cn10k_mldev->xstats.entries == NULL)
- cn10k_mldev->xstats.entries = rte_zmalloc(
- "cn10k_ml_xstats", sizeof(struct cnxk_ml_xstats_entry) * nb_stats,
- PLT_CACHE_LINE_SIZE);
-
- if (cn10k_mldev->xstats.entries == NULL)
- return -ENOMEM;
-
- /* Initialize device xstats */
- stat_id = 0;
- for (i = 0; i < RTE_DIM(device_xstats); i++) {
- cn10k_mldev->xstats.entries[stat_id].map.id = stat_id;
- snprintf(cn10k_mldev->xstats.entries[stat_id].map.name,
- sizeof(cn10k_mldev->xstats.entries[stat_id].map.name), "%s",
- device_xstats[i].name);
-
- cn10k_mldev->xstats.entries[stat_id].mode = RTE_ML_DEV_XSTATS_DEVICE;
- cn10k_mldev->xstats.entries[stat_id].type = device_xstats[i].type;
- cn10k_mldev->xstats.entries[stat_id].fn_id = CNXK_ML_XSTATS_FN_DEVICE;
- cn10k_mldev->xstats.entries[stat_id].obj_idx = 0;
- cn10k_mldev->xstats.entries[stat_id].reset_allowed = device_xstats[i].reset_allowed;
- stat_id++;
- }
- cn10k_mldev->xstats.count_mode_device = stat_id;
-
- /* Initialize model xstats */
- for (model = 0; model < ML_CNXK_MAX_MODELS; model++) {
- cn10k_mldev->xstats.offset_for_model[model] = stat_id;
-
- for (i = 0; i < RTE_DIM(layer_xstats); i++) {
- cn10k_mldev->xstats.entries[stat_id].map.id = stat_id;
- cn10k_mldev->xstats.entries[stat_id].mode = RTE_ML_DEV_XSTATS_MODEL;
- cn10k_mldev->xstats.entries[stat_id].type = layer_xstats[i].type;
- cn10k_mldev->xstats.entries[stat_id].fn_id = CNXK_ML_XSTATS_FN_MODEL;
- cn10k_mldev->xstats.entries[stat_id].obj_idx = model;
- cn10k_mldev->xstats.entries[stat_id].reset_allowed =
- layer_xstats[i].reset_allowed;
-
- /* Name of xstat is updated during model load */
- snprintf(cn10k_mldev->xstats.entries[stat_id].map.name,
- sizeof(cn10k_mldev->xstats.entries[stat_id].map.name),
- "Model-%u-%s", model, layer_xstats[i].name);
-
- stat_id++;
- }
-
- cn10k_mldev->xstats.count_per_model[model] = RTE_DIM(layer_xstats);
- }
-
- cn10k_mldev->xstats.count_mode_model = stat_id - cn10k_mldev->xstats.count_mode_device;
- cn10k_mldev->xstats.count = stat_id;
-
- return 0;
-}
-
static void
-cn10k_ml_xstats_uninit(struct rte_ml_dev *dev)
+cn10k_ml_xstats_layer_name_update(struct cnxk_ml_dev *cnxk_mldev, uint16_t model_id,
+ uint16_t layer_id)
{
- struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_dev *cnxk_mldev;
-
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
-
- rte_free(cn10k_mldev->xstats.entries);
- cn10k_mldev->xstats.entries = NULL;
-
- cn10k_mldev->xstats.count = 0;
-}
-
-static void
-cn10k_ml_xstats_model_name_update(struct rte_ml_dev *dev, uint16_t model_id)
-{
- struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_dev *cnxk_mldev;
struct cnxk_ml_model *model;
+ struct cnxk_ml_layer *layer;
uint16_t rclk_freq;
uint16_t sclk_freq;
uint16_t stat_id;
char suffix[8];
uint16_t i;
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
- model = dev->data->models[model_id];
- stat_id = RTE_DIM(device_xstats) + model_id * RTE_DIM(layer_xstats);
+ model = cnxk_mldev->mldev->data->models[model_id];
+ layer = &model->layer[layer_id];
+ stat_id = cnxk_mldev->xstats.offset_for_layer[model_id][layer_id];
roc_clk_freq_get(&rclk_freq, &sclk_freq);
if (sclk_freq == 0)
@@ -306,270 +220,94 @@ cn10k_ml_xstats_model_name_update(struct rte_ml_dev *dev, uint16_t model_id)
else
strcpy(suffix, "ns");
- /* Update xstat name based on model name and sclk availability */
+ /* Update xstat name based on layer name and sclk availability */
for (i = 0; i < RTE_DIM(layer_xstats); i++) {
- snprintf(cn10k_mldev->xstats.entries[stat_id].map.name,
- sizeof(cn10k_mldev->xstats.entries[stat_id].map.name), "%s-%s-%s",
- model->layer[0].glow.metadata.model.name, layer_xstats[i].name, suffix);
+ snprintf(cnxk_mldev->xstats.entries[stat_id].map.name,
+ sizeof(cnxk_mldev->xstats.entries[stat_id].map.name), "%s-%s-%s",
+ layer->glow.metadata.model.name, layer_xstats[i].name, suffix);
stat_id++;
}
}
-static uint64_t
-cn10k_ml_dev_xstat_get(struct rte_ml_dev *dev, uint16_t obj_idx __rte_unused,
- enum cnxk_ml_xstats_type type)
-{
- struct cnxk_ml_dev *cnxk_mldev;
-
- cnxk_mldev = dev->data->dev_private;
-
- switch (type) {
- case nb_models_loaded:
- return cnxk_mldev->nb_models_loaded;
- case nb_models_unloaded:
- return cnxk_mldev->nb_models_unloaded;
- case nb_models_started:
- return cnxk_mldev->nb_models_started;
- case nb_models_stopped:
- return cnxk_mldev->nb_models_stopped;
- default:
- return -1;
- }
-
- return 0;
-}
-
-#define ML_AVG_FOREACH_QP(dev, model, qp_id, str, value, count) \
+#define ML_AVG_FOREACH_QP(cnxk_mldev, layer, qp_id, str, value, count) \
do { \
value = 0; \
- for (qp_id = 0; qp_id < dev->data->nb_queue_pairs; qp_id++) { \
- value += model->layer[0].glow.burst_xstats[qp_id].str##_latency_tot; \
- count += model->layer[0].glow.burst_xstats[qp_id].dequeued_count - \
- model->layer[0].glow.burst_xstats[qp_id].str##_reset_count; \
+ for (qp_id = 0; qp_id < cnxk_mldev->mldev->data->nb_queue_pairs; qp_id++) { \
+ value += layer->glow.burst_xstats[qp_id].str##_latency_tot; \
+ count += layer->glow.burst_xstats[qp_id].dequeued_count - \
+ layer->glow.burst_xstats[qp_id].str##_reset_count; \
} \
+ value += layer->glow.sync_xstats->str##_latency_tot; \
+ count += layer->glow.sync_xstats->dequeued_count - \
+ layer->glow.sync_xstats->str##_reset_count; \
if (count != 0) \
value = value / count; \
} while (0)
-#define ML_MIN_FOREACH_QP(dev, model, qp_id, str, value, count) \
+#define ML_MIN_FOREACH_QP(cnxk_mldev, layer, qp_id, str, value, count) \
do { \
value = UINT64_MAX; \
- for (qp_id = 0; qp_id < dev->data->nb_queue_pairs; qp_id++) { \
- value = PLT_MIN( \
- value, \
- model->layer[0].glow.burst_xstats[qp_id].str##_latency_min); \
- count += model->layer[0].glow.burst_xstats[qp_id].dequeued_count - \
- model->layer[0].glow.burst_xstats[qp_id].str##_reset_count; \
+ for (qp_id = 0; qp_id < cnxk_mldev->mldev->data->nb_queue_pairs; qp_id++) { \
+ value = PLT_MIN(value, layer->glow.burst_xstats[qp_id].str##_latency_min); \
+ count += layer->glow.burst_xstats[qp_id].dequeued_count - \
+ layer->glow.burst_xstats[qp_id].str##_reset_count; \
} \
+ value = PLT_MIN(value, layer->glow.sync_xstats->str##_latency_min); \
+ count += layer->glow.sync_xstats->dequeued_count - \
+ layer->glow.sync_xstats->str##_reset_count; \
if (count == 0) \
value = 0; \
} while (0)
-#define ML_MAX_FOREACH_QP(dev, model, qp_id, str, value, count) \
+#define ML_MAX_FOREACH_QP(cnxk_mldev, layer, qp_id, str, value, count) \
do { \
value = 0; \
- for (qp_id = 0; qp_id < dev->data->nb_queue_pairs; qp_id++) { \
- value = PLT_MAX( \
- value, \
- model->layer[0].glow.burst_xstats[qp_id].str##_latency_max); \
- count += model->layer[0].glow.burst_xstats[qp_id].dequeued_count - \
- model->layer[0].glow.burst_xstats[qp_id].str##_reset_count; \
+ for (qp_id = 0; qp_id < cnxk_mldev->mldev->data->nb_queue_pairs; qp_id++) { \
+ value = PLT_MAX(value, layer->glow.burst_xstats[qp_id].str##_latency_max); \
+ count += layer->glow.burst_xstats[qp_id].dequeued_count - \
+ layer->glow.burst_xstats[qp_id].str##_reset_count; \
} \
+ value = PLT_MAX(value, layer->glow.sync_xstats->str##_latency_max); \
+ count += layer->glow.sync_xstats->dequeued_count - \
+ layer->glow.sync_xstats->str##_reset_count; \
if (count == 0) \
value = 0; \
} while (0)
-static uint64_t
-cn10k_ml_model_xstat_get(struct rte_ml_dev *dev, uint16_t obj_idx, enum cnxk_ml_xstats_type type)
+uint64_t
+cn10k_ml_model_xstat_get(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_layer *layer,
+ enum cnxk_ml_xstats_type type)
{
- struct cnxk_ml_model *model;
- uint16_t rclk_freq; /* MHz */
- uint16_t sclk_freq; /* MHz */
uint64_t count = 0;
- uint64_t value;
+ uint64_t value = 0;
uint32_t qp_id;
- model = dev->data->models[obj_idx];
- if (model == NULL)
- return 0;
-
switch (type) {
case avg_hw_latency:
- ML_AVG_FOREACH_QP(dev, model, qp_id, hw, value, count);
+ ML_AVG_FOREACH_QP(cnxk_mldev, layer, qp_id, hw, value, count);
break;
case min_hw_latency:
- ML_MIN_FOREACH_QP(dev, model, qp_id, hw, value, count);
+ ML_MIN_FOREACH_QP(cnxk_mldev, layer, qp_id, hw, value, count);
break;
case max_hw_latency:
- ML_MAX_FOREACH_QP(dev, model, qp_id, hw, value, count);
+ ML_MAX_FOREACH_QP(cnxk_mldev, layer, qp_id, hw, value, count);
break;
case avg_fw_latency:
- ML_AVG_FOREACH_QP(dev, model, qp_id, fw, value, count);
+ ML_AVG_FOREACH_QP(cnxk_mldev, layer, qp_id, fw, value, count);
break;
case min_fw_latency:
- ML_MIN_FOREACH_QP(dev, model, qp_id, fw, value, count);
+ ML_MIN_FOREACH_QP(cnxk_mldev, layer, qp_id, fw, value, count);
break;
case max_fw_latency:
- ML_MAX_FOREACH_QP(dev, model, qp_id, fw, value, count);
+ ML_MAX_FOREACH_QP(cnxk_mldev, layer, qp_id, fw, value, count);
break;
default:
value = 0;
}
- roc_clk_freq_get(&rclk_freq, &sclk_freq);
- if (sclk_freq != 0) /* return in ns */
- value = (value * 1000ULL) / sclk_freq;
-
return value;
}
-static int
-cn10k_ml_device_xstats_reset(struct rte_ml_dev *dev, const uint16_t stat_ids[], uint16_t nb_ids)
-{
- struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_xstats_entry *xs;
- struct cnxk_ml_dev *cnxk_mldev;
- uint16_t nb_stats;
- uint16_t stat_id;
- uint32_t i;
-
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
-
- if (stat_ids == NULL)
- nb_stats = cn10k_mldev->xstats.count_mode_device;
- else
- nb_stats = nb_ids;
-
- for (i = 0; i < nb_stats; i++) {
- if (stat_ids == NULL)
- stat_id = i;
- else
- stat_id = stat_ids[i];
-
- if (stat_id >= cn10k_mldev->xstats.count_mode_device)
- return -EINVAL;
-
- xs = &cn10k_mldev->xstats.entries[stat_id];
- if (!xs->reset_allowed)
- continue;
-
- xs->reset_value = cn10k_ml_dev_xstat_get(dev, xs->obj_idx, xs->type);
- }
-
- return 0;
-}
-
-#define ML_AVG_RESET_FOREACH_QP(dev, model, qp_id, str) \
- do { \
- for (qp_id = 0; qp_id < dev->data->nb_queue_pairs; qp_id++) { \
- model->layer[0].glow.burst_xstats[qp_id].str##_latency_tot = 0; \
- model->layer[0].glow.burst_xstats[qp_id].str##_reset_count = \
- model->layer[0].glow.burst_xstats[qp_id].dequeued_count; \
- } \
- } while (0)
-
-#define ML_MIN_RESET_FOREACH_QP(dev, model, qp_id, str) \
- do { \
- for (qp_id = 0; qp_id < dev->data->nb_queue_pairs; qp_id++) \
- model->layer[0].glow.burst_xstats[qp_id].str##_latency_min = UINT64_MAX; \
- } while (0)
-
-#define ML_MAX_RESET_FOREACH_QP(dev, model, qp_id, str) \
- do { \
- for (qp_id = 0; qp_id < dev->data->nb_queue_pairs; qp_id++) \
- model->layer[0].glow.burst_xstats[qp_id].str##_latency_max = 0; \
- } while (0)
-
-static void
-cn10k_ml_reset_model_stat(struct rte_ml_dev *dev, uint16_t model_id, enum cnxk_ml_xstats_type type)
-{
- struct cnxk_ml_model *model;
- uint32_t qp_id;
-
- model = dev->data->models[model_id];
-
- switch (type) {
- case avg_hw_latency:
- ML_AVG_RESET_FOREACH_QP(dev, model, qp_id, hw);
- break;
- case min_hw_latency:
- ML_MIN_RESET_FOREACH_QP(dev, model, qp_id, hw);
- break;
- case max_hw_latency:
- ML_MAX_RESET_FOREACH_QP(dev, model, qp_id, hw);
- break;
- case avg_fw_latency:
- ML_AVG_RESET_FOREACH_QP(dev, model, qp_id, fw);
- break;
- case min_fw_latency:
- ML_MIN_RESET_FOREACH_QP(dev, model, qp_id, fw);
- break;
- case max_fw_latency:
- ML_MAX_RESET_FOREACH_QP(dev, model, qp_id, fw);
- break;
- default:
- return;
- }
-}
-
-static int
-cn10k_ml_model_xstats_reset(struct rte_ml_dev *dev, int32_t model_id, const uint16_t stat_ids[],
- uint16_t nb_ids)
-{
- struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_xstats_entry *xs;
- struct cnxk_ml_dev *cnxk_mldev;
- struct cnxk_ml_model *model;
- int32_t lcl_model_id = 0;
- uint16_t start_id;
- uint16_t end_id;
- int32_t i;
- int32_t j;
-
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
- for (i = 0; i < ML_CNXK_MAX_MODELS; i++) {
- if (model_id == -1) {
- model = dev->data->models[i];
- if (model == NULL) /* Skip inactive models */
- continue;
- } else {
- if (model_id != i)
- continue;
-
- model = dev->data->models[model_id];
- if (model == NULL) {
- plt_err("Invalid model_id = %d\n", model_id);
- return -EINVAL;
- }
- }
-
- start_id = cn10k_mldev->xstats.offset_for_model[i];
- end_id = cn10k_mldev->xstats.offset_for_model[i] +
- cn10k_mldev->xstats.count_per_model[i] - 1;
-
- if (stat_ids == NULL) {
- for (j = start_id; j <= end_id; j++) {
- xs = &cn10k_mldev->xstats.entries[j];
- cn10k_ml_reset_model_stat(dev, i, xs->type);
- }
- } else {
- for (j = 0; j < nb_ids; j++) {
- if (stat_ids[j] < start_id || stat_ids[j] > end_id) {
- plt_err("Invalid stat_ids[%d] = %d for model_id = %d\n", j,
- stat_ids[j], lcl_model_id);
- return -EINVAL;
- }
- xs = &cn10k_mldev->xstats.entries[stat_ids[j]];
- cn10k_ml_reset_model_stat(dev, i, xs->type);
- }
- }
- }
-
- return 0;
-}
-
static int
cn10k_ml_cache_model_data(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_layer *layer)
{
@@ -654,7 +392,6 @@ cn10k_ml_dev_configure(struct cnxk_ml_dev *cnxk_mldev, const struct rte_ml_dev_c
struct cn10k_ml_dev *cn10k_mldev;
struct cn10k_ml_ocm *ocm;
uint16_t tile_id;
- int ret;
RTE_SET_USED(conf);
@@ -682,13 +419,6 @@ cn10k_ml_dev_configure(struct cnxk_ml_dev *cnxk_mldev, const struct rte_ml_dev_c
rte_spinlock_init(&ocm->lock);
- /* Initialize xstats */
- ret = cn10k_ml_xstats_init(cnxk_mldev->mldev);
- if (ret != 0) {
- plt_err("Failed to initialize xstats");
- return ret;
- }
-
/* Set JCMDQ enqueue function */
if (cn10k_mldev->hw_queue_lock == 1)
cn10k_mldev->ml_jcmdq_enqueue = roc_ml_jcmdq_enqueue_sl;
@@ -717,9 +447,6 @@ cn10k_ml_dev_close(struct cnxk_ml_dev *cnxk_mldev)
/* Release ocm_mask memory */
rte_free(cn10k_mldev->ocm.ocm_mask);
- /* Un-initialize xstats */
- cn10k_ml_xstats_uninit(cnxk_mldev->mldev);
-
/* Unload firmware */
cn10k_ml_fw_unload(cnxk_mldev);
@@ -770,174 +497,6 @@ cn10k_ml_dev_stop(struct cnxk_ml_dev *cnxk_mldev)
return 0;
}
-int
-cn10k_ml_dev_xstats_names_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode,
- int32_t model_id, struct rte_ml_dev_xstats_map *xstats_map,
- uint32_t size)
-{
- struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_dev *cnxk_mldev;
- uint32_t xstats_mode_count;
- uint32_t idx = 0;
- uint32_t i;
-
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
-
- xstats_mode_count = 0;
- switch (mode) {
- case RTE_ML_DEV_XSTATS_DEVICE:
- xstats_mode_count = cn10k_mldev->xstats.count_mode_device;
- break;
- case RTE_ML_DEV_XSTATS_MODEL:
- if (model_id >= ML_CNXK_MAX_MODELS)
- break;
- xstats_mode_count = cn10k_mldev->xstats.count_per_model[model_id];
- break;
- default:
- return -EINVAL;
- };
-
- if (xstats_mode_count > size || xstats_map == NULL)
- return xstats_mode_count;
-
- for (i = 0; i < cn10k_mldev->xstats.count && idx < size; i++) {
- if (cn10k_mldev->xstats.entries[i].mode != mode)
- continue;
-
- if (mode != RTE_ML_DEV_XSTATS_DEVICE &&
- model_id != cn10k_mldev->xstats.entries[i].obj_idx)
- continue;
-
- strncpy(xstats_map[idx].name, cn10k_mldev->xstats.entries[i].map.name,
- RTE_ML_STR_MAX);
- xstats_map[idx].id = cn10k_mldev->xstats.entries[i].map.id;
- idx++;
- }
-
- return idx;
-}
-
-int
-cn10k_ml_dev_xstats_by_name_get(struct rte_ml_dev *dev, const char *name, uint16_t *stat_id,
- uint64_t *value)
-{
- struct cnxk_ml_xstats_entry *xs;
- struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_dev *cnxk_mldev;
- cnxk_ml_xstats_fn fn;
- uint32_t i;
-
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
- for (i = 0; i < cn10k_mldev->xstats.count; i++) {
- xs = &cn10k_mldev->xstats.entries[i];
- if (strncmp(xs->map.name, name, RTE_ML_STR_MAX) == 0) {
- if (stat_id != NULL)
- *stat_id = xs->map.id;
-
- switch (xs->fn_id) {
- case CNXK_ML_XSTATS_FN_DEVICE:
- fn = cn10k_ml_dev_xstat_get;
- break;
- case CNXK_ML_XSTATS_FN_MODEL:
- fn = cn10k_ml_model_xstat_get;
- break;
- default:
- plt_err("Unexpected xstat fn_id = %d", xs->fn_id);
- return -EINVAL;
- }
-
- *value = fn(dev, xs->obj_idx, xs->type) - xs->reset_value;
-
- return 0;
- }
- }
-
- if (stat_id != NULL)
- *stat_id = (uint16_t)-1;
-
- return -EINVAL;
-}
-
-int
-cn10k_ml_dev_xstats_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode, int32_t model_id,
- const uint16_t stat_ids[], uint64_t values[], uint16_t nb_ids)
-{
- struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_xstats_entry *xs;
- struct cnxk_ml_dev *cnxk_mldev;
- uint32_t xstats_mode_count;
- cnxk_ml_xstats_fn fn;
- uint64_t val;
- uint32_t idx;
- uint32_t i;
-
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
- xstats_mode_count = 0;
-
- switch (mode) {
- case RTE_ML_DEV_XSTATS_DEVICE:
- xstats_mode_count = cn10k_mldev->xstats.count_mode_device;
- break;
- case RTE_ML_DEV_XSTATS_MODEL:
- if (model_id >= ML_CNXK_MAX_MODELS)
- return -EINVAL;
- xstats_mode_count = cn10k_mldev->xstats.count_per_model[model_id];
- break;
- default:
- return -EINVAL;
- };
-
- idx = 0;
- for (i = 0; i < nb_ids && idx < xstats_mode_count; i++) {
- xs = &cn10k_mldev->xstats.entries[stat_ids[i]];
- if (stat_ids[i] > cn10k_mldev->xstats.count || xs->mode != mode)
- continue;
-
- if (mode == RTE_ML_DEV_XSTATS_MODEL && model_id != xs->obj_idx) {
- plt_err("Invalid stats_id[%d] = %d for model_id = %d\n", i, stat_ids[i],
- model_id);
- return -EINVAL;
- }
-
- switch (xs->fn_id) {
- case CNXK_ML_XSTATS_FN_DEVICE:
- fn = cn10k_ml_dev_xstat_get;
- break;
- case CNXK_ML_XSTATS_FN_MODEL:
- fn = cn10k_ml_model_xstat_get;
- break;
- default:
- plt_err("Unexpected xstat fn_id = %d", xs->fn_id);
- return -EINVAL;
- }
-
- val = fn(dev, xs->obj_idx, xs->type);
- if (values)
- values[idx] = val;
-
- idx++;
- }
-
- return idx;
-}
-
-int
-cn10k_ml_dev_xstats_reset(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode,
- int32_t model_id, const uint16_t stat_ids[], uint16_t nb_ids)
-{
- switch (mode) {
- case RTE_ML_DEV_XSTATS_DEVICE:
- return cn10k_ml_device_xstats_reset(dev, stat_ids, nb_ids);
- case RTE_ML_DEV_XSTATS_MODEL:
- return cn10k_ml_model_xstats_reset(dev, model_id, stat_ids, nb_ids);
- };
-
- return 0;
-}
-
int
cn10k_ml_dev_dump(struct cnxk_ml_dev *cnxk_mldev, FILE *fp)
{
@@ -1211,7 +770,7 @@ cn10k_ml_layer_load(void *device, uint16_t model_id, const char *layer_name, uin
sizeof(struct cn10k_ml_layer_xstats));
/* Update xstats names */
- cn10k_ml_xstats_model_name_update(cnxk_mldev->mldev, idx);
+ cn10k_ml_xstats_layer_name_update(cnxk_mldev, model_id, layer_id);
layer->state = ML_CNXK_LAYER_STATE_LOADED;
cnxk_mldev->index_map[idx].model_id = model->model_id;
diff --git a/drivers/ml/cnxk/cn10k_ml_ops.h b/drivers/ml/cnxk/cn10k_ml_ops.h
index 47e7cb12af..4d76164dba 100644
--- a/drivers/ml/cnxk/cn10k_ml_ops.h
+++ b/drivers/ml/cnxk/cn10k_ml_ops.h
@@ -13,6 +13,7 @@
struct cnxk_ml_dev;
struct cnxk_ml_qp;
struct cnxk_ml_model;
+struct cnxk_ml_layer;
/* Firmware version string length */
#define MLDEV_FIRMWARE_VERSION_LENGTH 32
@@ -298,17 +299,6 @@ int cn10k_ml_dev_stop(struct cnxk_ml_dev *cnxk_mldev);
int cn10k_ml_dev_dump(struct cnxk_ml_dev *cnxk_mldev, FILE *fp);
int cn10k_ml_dev_selftest(struct cnxk_ml_dev *cnxk_mldev);
-int cn10k_ml_dev_xstats_names_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode,
- int32_t model_id, struct rte_ml_dev_xstats_map *xstats_map,
- uint32_t size);
-int cn10k_ml_dev_xstats_by_name_get(struct rte_ml_dev *dev, const char *name, uint16_t *stat_id,
- uint64_t *value);
-int cn10k_ml_dev_xstats_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode,
- int32_t model_id, const uint16_t stat_ids[], uint64_t values[],
- uint16_t nb_ids);
-int cn10k_ml_dev_xstats_reset(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode,
- int32_t model_id, const uint16_t stat_ids[], uint16_t nb_ids);
-
/* Slow-path ops */
int cn10k_ml_model_load(struct cnxk_ml_dev *cnxk_mldev, struct rte_ml_model_params *params,
struct cnxk_ml_model *model);
@@ -337,4 +327,8 @@ int cn10k_ml_layer_unload(void *device, uint16_t model_id, const char *layer_nam
int cn10k_ml_layer_start(void *device, uint16_t model_id, const char *layer_name);
int cn10k_ml_layer_stop(void *device, uint16_t model_id, const char *layer_name);
+/* xstats ops */
+uint64_t cn10k_ml_model_xstat_get(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_layer *layer,
+ enum cnxk_ml_xstats_type type);
+
#endif /* _CN10K_ML_OPS_H_ */
diff --git a/drivers/ml/cnxk/cnxk_ml_dev.h b/drivers/ml/cnxk/cnxk_ml_dev.h
index 1590249abd..3ce9338f1f 100644
--- a/drivers/ml/cnxk/cnxk_ml_dev.h
+++ b/drivers/ml/cnxk/cnxk_ml_dev.h
@@ -9,6 +9,8 @@
#include "cn10k_ml_dev.h"
+#include "cnxk_ml_xstats.h"
+
/* ML command timeout in seconds */
#define ML_CNXK_CMD_TIMEOUT 5
@@ -51,6 +53,9 @@ struct cnxk_ml_dev {
/* Configuration state */
enum cnxk_ml_dev_state state;
+ /* Extended stats data */
+ struct cnxk_ml_xstats xstats;
+
/* Number of models loaded */
uint16_t nb_models_loaded;
diff --git a/drivers/ml/cnxk/cnxk_ml_ops.c b/drivers/ml/cnxk/cnxk_ml_ops.c
index c75317d6da..6a423d9eda 100644
--- a/drivers/ml/cnxk/cnxk_ml_ops.c
+++ b/drivers/ml/cnxk/cnxk_ml_ops.c
@@ -115,6 +115,285 @@ cnxk_ml_qp_create(const struct rte_ml_dev *dev, uint16_t qp_id, uint32_t nb_desc
return NULL;
}
+static int
+cnxk_ml_xstats_init(struct cnxk_ml_dev *cnxk_mldev)
+{
+ uint16_t nb_stats;
+ uint16_t stat_id;
+ uint16_t model;
+ uint16_t layer;
+ uint16_t i;
+
+ /* Allocate memory for xstats entries. Don't allocate during reconfigure */
+ nb_stats = RTE_DIM(device_xstats) +
+ RTE_DIM(layer_xstats) * ML_CNXK_MAX_MODELS * ML_CNXK_MODEL_MAX_LAYERS;
+ if (cnxk_mldev->xstats.entries == NULL)
+ cnxk_mldev->xstats.entries = rte_zmalloc(
+ "cnxk_ml_xstats", sizeof(struct cnxk_ml_xstats_entry) * nb_stats,
+ PLT_CACHE_LINE_SIZE);
+
+ if (cnxk_mldev->xstats.entries == NULL)
+ return -ENOMEM;
+
+ /* Initialize device xstats */
+ stat_id = 0;
+ for (i = 0; i < RTE_DIM(device_xstats); i++) {
+ cnxk_mldev->xstats.entries[stat_id].map.id = stat_id;
+ snprintf(cnxk_mldev->xstats.entries[stat_id].map.name,
+ sizeof(cnxk_mldev->xstats.entries[stat_id].map.name), "%s",
+ device_xstats[i].name);
+
+ cnxk_mldev->xstats.entries[stat_id].mode = RTE_ML_DEV_XSTATS_DEVICE;
+ cnxk_mldev->xstats.entries[stat_id].group = CNXK_ML_XSTATS_GROUP_DEVICE;
+ cnxk_mldev->xstats.entries[stat_id].type = device_xstats[i].type;
+ cnxk_mldev->xstats.entries[stat_id].fn_id = CNXK_ML_XSTATS_FN_DEVICE;
+ cnxk_mldev->xstats.entries[stat_id].obj_idx = 0;
+ cnxk_mldev->xstats.entries[stat_id].reset_allowed = device_xstats[i].reset_allowed;
+ stat_id++;
+ }
+ cnxk_mldev->xstats.count_mode_device = stat_id;
+
+ /* Initialize model xstats */
+ for (model = 0; model < ML_CNXK_MAX_MODELS; model++) {
+ cnxk_mldev->xstats.offset_for_model[model] = stat_id;
+
+ for (layer = 0; layer < ML_CNXK_MODEL_MAX_LAYERS; layer++) {
+ cnxk_mldev->xstats.offset_for_layer[model][layer] = stat_id;
+
+ for (i = 0; i < RTE_DIM(layer_xstats); i++) {
+ cnxk_mldev->xstats.entries[stat_id].map.id = stat_id;
+ cnxk_mldev->xstats.entries[stat_id].mode = RTE_ML_DEV_XSTATS_MODEL;
+ cnxk_mldev->xstats.entries[stat_id].group =
+ CNXK_ML_XSTATS_GROUP_LAYER;
+ cnxk_mldev->xstats.entries[stat_id].type = layer_xstats[i].type;
+ cnxk_mldev->xstats.entries[stat_id].fn_id = CNXK_ML_XSTATS_FN_MODEL;
+ cnxk_mldev->xstats.entries[stat_id].obj_idx = model;
+ cnxk_mldev->xstats.entries[stat_id].layer_id = layer;
+ cnxk_mldev->xstats.entries[stat_id].reset_allowed =
+ layer_xstats[i].reset_allowed;
+
+ /* Name of xstat is updated during model load */
+ snprintf(cnxk_mldev->xstats.entries[stat_id].map.name,
+ sizeof(cnxk_mldev->xstats.entries[stat_id].map.name),
+ "Layer-%u-%u-%s", model, layer, layer_xstats[i].name);
+
+ stat_id++;
+ }
+
+ cnxk_mldev->xstats.count_per_layer[model][layer] = RTE_DIM(layer_xstats);
+ }
+
+ cnxk_mldev->xstats.count_per_model[model] = RTE_DIM(layer_xstats);
+ }
+
+ cnxk_mldev->xstats.count_mode_model = stat_id - cnxk_mldev->xstats.count_mode_device;
+ cnxk_mldev->xstats.count = stat_id;
+
+ return 0;
+}
+
+static void
+cnxk_ml_xstats_uninit(struct cnxk_ml_dev *cnxk_mldev)
+{
+ rte_free(cnxk_mldev->xstats.entries);
+ cnxk_mldev->xstats.entries = NULL;
+
+ cnxk_mldev->xstats.count = 0;
+}
+
+static uint64_t
+cnxk_ml_dev_xstat_get(struct cnxk_ml_dev *cnxk_mldev, uint16_t obj_idx __rte_unused,
+ int32_t layer_id __rte_unused, enum cnxk_ml_xstats_type type)
+{
+ switch (type) {
+ case nb_models_loaded:
+ return cnxk_mldev->nb_models_loaded;
+ case nb_models_unloaded:
+ return cnxk_mldev->nb_models_unloaded;
+ case nb_models_started:
+ return cnxk_mldev->nb_models_started;
+ case nb_models_stopped:
+ return cnxk_mldev->nb_models_stopped;
+ default:
+ return -1;
+ }
+
+ return 0;
+}
+
+static uint64_t
+cnxk_ml_model_xstat_get(struct cnxk_ml_dev *cnxk_mldev, uint16_t obj_idx, int32_t layer_id,
+ enum cnxk_ml_xstats_type type)
+{
+ struct cnxk_ml_model *model;
+ struct cnxk_ml_layer *layer;
+ uint16_t rclk_freq; /* MHz */
+ uint16_t sclk_freq; /* MHz */
+ uint64_t value = 0;
+
+ model = cnxk_mldev->mldev->data->models[obj_idx];
+ if (model == NULL)
+ return 0;
+
+ if (layer_id >= 0)
+ layer = &model->layer[layer_id];
+ else
+ return 0;
+
+ value = cn10k_ml_model_xstat_get(cnxk_mldev, layer, type);
+
+ roc_clk_freq_get(&rclk_freq, &sclk_freq);
+ if (sclk_freq != 0) /* return in ns */
+ value = (value * 1000ULL) / sclk_freq;
+
+ return value;
+}
+
+static int
+cnxk_ml_device_xstats_reset(struct cnxk_ml_dev *cnxk_mldev, const uint16_t stat_ids[],
+ uint16_t nb_ids)
+{
+ struct cnxk_ml_xstats_entry *xs;
+ uint16_t nb_stats;
+ uint16_t stat_id;
+ uint32_t i;
+
+ if (stat_ids == NULL)
+ nb_stats = cnxk_mldev->xstats.count_mode_device;
+ else
+ nb_stats = nb_ids;
+
+ for (i = 0; i < nb_stats; i++) {
+ if (stat_ids == NULL)
+ stat_id = i;
+ else
+ stat_id = stat_ids[i];
+
+ if (stat_id >= cnxk_mldev->xstats.count_mode_device)
+ return -EINVAL;
+
+ xs = &cnxk_mldev->xstats.entries[stat_id];
+ if (!xs->reset_allowed)
+ continue;
+
+ xs->reset_value =
+ cnxk_ml_dev_xstat_get(cnxk_mldev, xs->obj_idx, xs->layer_id, xs->type);
+ }
+
+ return 0;
+}
+
+#define ML_AVG_RESET_FOREACH_QP(cnxk_mldev, layer, qp_id, str) \
+ do { \
+ for (qp_id = 0; qp_id < cnxk_mldev->mldev->data->nb_queue_pairs; qp_id++) { \
+ layer->glow.burst_xstats[qp_id].str##_latency_tot = 0; \
+ layer->glow.burst_xstats[qp_id].str##_reset_count = \
+ layer->glow.burst_xstats[qp_id].dequeued_count; \
+ } \
+ } while (0)
+
+#define ML_MIN_RESET_FOREACH_QP(cnxk_mldev, layer, qp_id, str) \
+ do { \
+ for (qp_id = 0; qp_id < cnxk_mldev->mldev->data->nb_queue_pairs; qp_id++) \
+ layer->glow.burst_xstats[qp_id].str##_latency_min = UINT64_MAX; \
+ } while (0)
+
+#define ML_MAX_RESET_FOREACH_QP(cnxk_mldev, layer, qp_id, str) \
+ do { \
+ for (qp_id = 0; qp_id < cnxk_mldev->mldev->data->nb_queue_pairs; qp_id++) \
+ layer->glow.burst_xstats[qp_id].str##_latency_max = 0; \
+ } while (0)
+
+static void
+cnxk_ml_reset_model_stat(struct cnxk_ml_dev *cnxk_mldev, uint16_t model_id,
+ enum cnxk_ml_xstats_type type)
+{
+ struct cnxk_ml_model *model;
+ struct cnxk_ml_layer *layer;
+ uint16_t layer_id = 0;
+ uint32_t qp_id;
+
+ model = cnxk_mldev->mldev->data->models[model_id];
+ layer = &model->layer[layer_id];
+
+ switch (type) {
+ case avg_hw_latency:
+ ML_AVG_RESET_FOREACH_QP(cnxk_mldev, layer, qp_id, hw);
+ break;
+ case min_hw_latency:
+ ML_MIN_RESET_FOREACH_QP(cnxk_mldev, layer, qp_id, hw);
+ break;
+ case max_hw_latency:
+ ML_MAX_RESET_FOREACH_QP(cnxk_mldev, layer, qp_id, hw);
+ break;
+ case avg_fw_latency:
+ ML_AVG_RESET_FOREACH_QP(cnxk_mldev, layer, qp_id, fw);
+ break;
+ case min_fw_latency:
+ ML_MIN_RESET_FOREACH_QP(cnxk_mldev, layer, qp_id, fw);
+ break;
+ case max_fw_latency:
+ ML_MAX_RESET_FOREACH_QP(cnxk_mldev, layer, qp_id, fw);
+ break;
+ default:
+ return;
+ }
+}
+
+static int
+cnxk_ml_model_xstats_reset(struct cnxk_ml_dev *cnxk_mldev, int32_t model_id,
+ const uint16_t stat_ids[], uint16_t nb_ids)
+{
+ struct cnxk_ml_xstats_entry *xs;
+ struct cnxk_ml_model *model;
+ int32_t lcl_model_id = 0;
+ uint16_t layer_id = 0;
+ uint16_t start_id;
+ uint16_t end_id;
+ int32_t i;
+ int32_t j;
+
+ for (i = 0; i < ML_CNXK_MAX_MODELS; i++) {
+ if (model_id == -1) {
+ model = cnxk_mldev->mldev->data->models[i];
+ if (model == NULL) /* skip inactive models */
+ continue;
+ } else {
+ if (model_id != i)
+ continue;
+
+ model = cnxk_mldev->mldev->data->models[model_id];
+ if (model == NULL) {
+ plt_err("Invalid model_id = %d\n", model_id);
+ return -EINVAL;
+ }
+ }
+
+ start_id = cnxk_mldev->xstats.offset_for_layer[i][layer_id];
+ end_id = cnxk_mldev->xstats.offset_for_layer[i][layer_id] +
+ cnxk_mldev->xstats.count_per_layer[i][layer_id] - 1;
+
+ if (stat_ids == NULL) {
+ for (j = start_id; j <= end_id; j++) {
+ xs = &cnxk_mldev->xstats.entries[j];
+ cnxk_ml_reset_model_stat(cnxk_mldev, i, xs->type);
+ }
+ } else {
+ for (j = 0; j < nb_ids; j++) {
+ if (stat_ids[j] < start_id || stat_ids[j] > end_id) {
+ plt_err("Invalid stat_ids[%d] = %d for model_id = %d\n", j,
+ stat_ids[j], lcl_model_id);
+ return -EINVAL;
+ }
+ xs = &cnxk_mldev->xstats.entries[stat_ids[j]];
+ cnxk_ml_reset_model_stat(cnxk_mldev, i, xs->type);
+ }
+ }
+ }
+
+ return 0;
+}
+
static int
cnxk_ml_dev_info_get(struct rte_ml_dev *dev, struct rte_ml_dev_info *dev_info)
{
@@ -294,6 +573,13 @@ cnxk_ml_dev_configure(struct rte_ml_dev *dev, const struct rte_ml_dev_config *co
for (i = 0; i < cnxk_mldev->max_nb_layers; i++)
cnxk_mldev->index_map[i].active = false;
+ /* Initialize xstats */
+ ret = cnxk_ml_xstats_init(cnxk_mldev);
+ if (ret != 0) {
+ plt_err("Failed to initialize xstats");
+ goto error;
+ }
+
cnxk_mldev->nb_models_loaded = 0;
cnxk_mldev->nb_models_started = 0;
cnxk_mldev->nb_models_stopped = 0;
@@ -323,6 +609,9 @@ cnxk_ml_dev_close(struct rte_ml_dev *dev)
cnxk_mldev = dev->data->dev_private;
+ /* Un-initialize xstats */
+ cnxk_ml_xstats_uninit(cnxk_mldev);
+
if (cn10k_ml_dev_close(cnxk_mldev) != 0)
plt_err("Failed to close CN10K ML Device");
@@ -521,6 +810,190 @@ cnxk_ml_dev_stats_reset(struct rte_ml_dev *dev)
}
}
+static int
+cnxk_ml_dev_xstats_names_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode,
+ int32_t model_id, struct rte_ml_dev_xstats_map *xstats_map,
+ uint32_t size)
+{
+ struct cnxk_ml_xstats_entry *xs;
+ struct cnxk_ml_dev *cnxk_mldev;
+ uint32_t xstats_mode_count;
+ uint16_t layer_id = 0;
+ uint32_t idx = 0;
+ uint32_t i;
+
+ if (dev == NULL)
+ return -EINVAL;
+
+ cnxk_mldev = dev->data->dev_private;
+ xstats_mode_count = 0;
+
+ switch (mode) {
+ case RTE_ML_DEV_XSTATS_DEVICE:
+ xstats_mode_count = cnxk_mldev->xstats.count_mode_device;
+ break;
+ case RTE_ML_DEV_XSTATS_MODEL:
+ if (model_id >= ML_CNXK_MAX_MODELS)
+ break;
+ xstats_mode_count = cnxk_mldev->xstats.count_per_layer[model_id][layer_id];
+ break;
+ default:
+ return -EINVAL;
+ };
+
+ if (xstats_mode_count > size || xstats_map == NULL)
+ return xstats_mode_count;
+
+ for (i = 0; i < cnxk_mldev->xstats.count && idx < size; i++) {
+ xs = &cnxk_mldev->xstats.entries[i];
+ if (xs->mode != mode)
+ continue;
+
+ if (mode == RTE_ML_DEV_XSTATS_MODEL &&
+ (model_id != xs->obj_idx || layer_id != xs->layer_id))
+ continue;
+
+ strncpy(xstats_map[idx].name, xs->map.name, RTE_ML_STR_MAX);
+ xstats_map[idx].id = xs->map.id;
+ idx++;
+ }
+
+ return idx;
+}
+
+static int
+cnxk_ml_dev_xstats_by_name_get(struct rte_ml_dev *dev, const char *name, uint16_t *stat_id,
+ uint64_t *value)
+{
+ struct cnxk_ml_xstats_entry *xs;
+ struct cnxk_ml_dev *cnxk_mldev;
+ cnxk_ml_xstats_fn fn;
+ uint32_t i;
+
+ if (dev == NULL)
+ return -EINVAL;
+
+ cnxk_mldev = dev->data->dev_private;
+
+ for (i = 0; i < cnxk_mldev->xstats.count; i++) {
+ xs = &cnxk_mldev->xstats.entries[i];
+ if (strncmp(xs->map.name, name, RTE_ML_STR_MAX) == 0) {
+ if (stat_id != NULL)
+ *stat_id = xs->map.id;
+
+ switch (xs->fn_id) {
+ case CNXK_ML_XSTATS_FN_DEVICE:
+ fn = cnxk_ml_dev_xstat_get;
+ break;
+ case CNXK_ML_XSTATS_FN_MODEL:
+ fn = cnxk_ml_model_xstat_get;
+ break;
+ default:
+ plt_err("Unexpected xstat fn_id = %d", xs->fn_id);
+ return -EINVAL;
+ }
+
+ *value = fn(cnxk_mldev, xs->obj_idx, xs->layer_id, xs->type) -
+ xs->reset_value;
+
+ return 0;
+ }
+ }
+
+ if (stat_id != NULL)
+ *stat_id = (uint16_t)-1;
+
+ return -EINVAL;
+}
+
+static int
+cnxk_ml_dev_xstats_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode, int32_t model_id,
+ const uint16_t stat_ids[], uint64_t values[], uint16_t nb_ids)
+{
+ struct cnxk_ml_xstats_entry *xs;
+ struct cnxk_ml_dev *cnxk_mldev;
+ uint32_t xstats_mode_count;
+ uint16_t layer_id = 0;
+ cnxk_ml_xstats_fn fn;
+ uint64_t val;
+ uint32_t idx;
+ uint32_t i;
+
+ if (dev == NULL)
+ return -EINVAL;
+
+ cnxk_mldev = dev->data->dev_private;
+ xstats_mode_count = 0;
+
+ switch (mode) {
+ case RTE_ML_DEV_XSTATS_DEVICE:
+ xstats_mode_count = cnxk_mldev->xstats.count_mode_device;
+ break;
+ case RTE_ML_DEV_XSTATS_MODEL:
+ if (model_id >= ML_CNXK_MAX_MODELS)
+ return -EINVAL;
+ xstats_mode_count = cnxk_mldev->xstats.count_per_layer[model_id][layer_id];
+ break;
+ default:
+ return -EINVAL;
+ };
+
+ idx = 0;
+ for (i = 0; i < nb_ids && idx < xstats_mode_count; i++) {
+ xs = &cnxk_mldev->xstats.entries[stat_ids[i]];
+ if (stat_ids[i] > cnxk_mldev->xstats.count || xs->mode != mode)
+ continue;
+
+ if (mode == RTE_ML_DEV_XSTATS_MODEL &&
+ (model_id != xs->obj_idx || layer_id != xs->layer_id)) {
+ plt_err("Invalid stats_id[%d] = %d for model_id = %d\n", i, stat_ids[i],
+ model_id);
+ return -EINVAL;
+ }
+
+ switch (xs->fn_id) {
+ case CNXK_ML_XSTATS_FN_DEVICE:
+ fn = cnxk_ml_dev_xstat_get;
+ break;
+ case CNXK_ML_XSTATS_FN_MODEL:
+ fn = cnxk_ml_model_xstat_get;
+ break;
+ default:
+ plt_err("Unexpected xstat fn_id = %d", xs->fn_id);
+ return -EINVAL;
+ }
+
+ val = fn(cnxk_mldev, xs->obj_idx, xs->layer_id, xs->type);
+ if (values)
+ values[idx] = val;
+
+ idx++;
+ }
+
+ return idx;
+}
+
+static int
+cnxk_ml_dev_xstats_reset(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode, int32_t model_id,
+ const uint16_t stat_ids[], uint16_t nb_ids)
+{
+ struct cnxk_ml_dev *cnxk_mldev;
+
+ if (dev == NULL)
+ return -EINVAL;
+
+ cnxk_mldev = dev->data->dev_private;
+
+ switch (mode) {
+ case RTE_ML_DEV_XSTATS_DEVICE:
+ return cnxk_ml_device_xstats_reset(cnxk_mldev, stat_ids, nb_ids);
+ case RTE_ML_DEV_XSTATS_MODEL:
+ return cnxk_ml_model_xstats_reset(cnxk_mldev, model_id, stat_ids, nb_ids);
+ };
+
+ return 0;
+}
+
static int
cnxk_ml_model_load(struct rte_ml_dev *dev, struct rte_ml_model_params *params, uint16_t *model_id)
{
@@ -806,10 +1279,10 @@ struct rte_ml_dev_ops cnxk_ml_ops = {
/* Stats ops */
.dev_stats_get = cnxk_ml_dev_stats_get,
.dev_stats_reset = cnxk_ml_dev_stats_reset,
- .dev_xstats_names_get = cn10k_ml_dev_xstats_names_get,
- .dev_xstats_by_name_get = cn10k_ml_dev_xstats_by_name_get,
- .dev_xstats_get = cn10k_ml_dev_xstats_get,
- .dev_xstats_reset = cn10k_ml_dev_xstats_reset,
+ .dev_xstats_names_get = cnxk_ml_dev_xstats_names_get,
+ .dev_xstats_by_name_get = cnxk_ml_dev_xstats_by_name_get,
+ .dev_xstats_get = cnxk_ml_dev_xstats_get,
+ .dev_xstats_reset = cnxk_ml_dev_xstats_reset,
/* Model ops */
.model_load = cnxk_ml_model_load,
diff --git a/drivers/ml/cnxk/cnxk_ml_xstats.h b/drivers/ml/cnxk/cnxk_ml_xstats.h
index 0d405679ca..5e02bb876c 100644
--- a/drivers/ml/cnxk/cnxk_ml_xstats.h
+++ b/drivers/ml/cnxk/cnxk_ml_xstats.h
@@ -7,6 +7,8 @@
#include "cnxk_ml_io.h"
+struct cnxk_ml_dev;
+
/* Extended stats types enum */
enum cnxk_ml_xstats_type {
/* Number of models loaded */
@@ -58,9 +60,21 @@ enum cnxk_ml_xstats_fn_type {
CNXK_ML_XSTATS_FN_MODEL,
};
+/* Extended stats group */
+enum cnxk_ml_xstats_group {
+ /* Device stats */
+ CNXK_ML_XSTATS_GROUP_DEVICE,
+
+ /* Model stats */
+ CNXK_ML_XSTATS_GROUP_MODEL,
+
+ /* Layer stats */
+ CNXK_ML_XSTATS_GROUP_LAYER,
+};
+
/* Function pointer to get xstats for a type */
-typedef uint64_t (*cnxk_ml_xstats_fn)(struct rte_ml_dev *cnxk_mldev, uint16_t obj_idx,
- enum cnxk_ml_xstats_type stat);
+typedef uint64_t (*cnxk_ml_xstats_fn)(struct cnxk_ml_dev *cnxk_mldev, uint16_t obj_idx,
+ int32_t layer_id, enum cnxk_ml_xstats_type stat);
/* Extended stats entry structure */
struct cnxk_ml_xstats_entry {
@@ -70,6 +84,9 @@ struct cnxk_ml_xstats_entry {
/* xstats mode, device or model */
enum rte_ml_dev_xstats_mode mode;
+ /* xstats group */
+ enum cnxk_ml_xstats_group group;
+
/* Type of xstats */
enum cnxk_ml_xstats_type type;
--
2.41.0
next prev parent reply other threads:[~2023-09-27 18:33 UTC|newest]
Thread overview: 340+ messages / expand[flat|nested] mbox.gz Atom feed top
2023-08-30 15:58 [PATCH v1 00/34] Implemenation of revised ml/cnxk driver Srikanth Yalavarthi
2023-08-30 15:58 ` [PATCH v1 01/34] ml/cnxk: drop support for register polling Srikanth Yalavarthi
2023-08-30 15:58 ` [PATCH v1 02/34] ml/cnxk: drop use of RTE API for firmware read Srikanth Yalavarthi
2023-09-21 12:08 ` Jerin Jacob
2023-09-21 12:52 ` David Marchand
2023-09-21 13:06 ` [EXT] " Srikanth Yalavarthi
2023-09-21 13:26 ` David Marchand
2023-09-22 3:59 ` Srikanth Yalavarthi
2023-09-22 8:07 ` David Marchand
2023-09-22 16:59 ` Srikanth Yalavarthi
2023-09-27 9:38 ` David Marchand
2023-09-27 10:00 ` [EXT] " Srikanth Yalavarthi
2023-09-27 18:37 ` Srikanth Yalavarthi
2023-08-30 15:58 ` [PATCH v1 03/34] ml/cnxk: add generic cnxk device structure Srikanth Yalavarthi
2023-08-30 15:58 ` [PATCH v1 04/34] ml/cnxk: add generic model and layer structures Srikanth Yalavarthi
2023-08-30 15:58 ` [PATCH v1 05/34] ml/cnxk: add generic cnxk request structure Srikanth Yalavarthi
2023-08-30 15:58 ` [PATCH v1 06/34] ml/cnxk: add generic cnxk xstats structures Srikanth Yalavarthi
2023-08-30 15:58 ` [PATCH v1 07/34] ml/cnxk: rename cnxk ops function pointers struct Srikanth Yalavarthi
2023-08-30 15:58 ` [PATCH v1 08/34] ml/cnxk: update device handling functions Srikanth Yalavarthi
2023-08-30 15:58 ` [PATCH v1 09/34] ml/cnxk: update queue-pair " Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 10/34] ml/cnxk: update model load and unload functions Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 11/34] ml/cnxk: update model start and stop functions Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 12/34] ml/cnxk: update model utility functions Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 13/34] ml/cnxk: update data quantization functions Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 14/34] ml/cnxk: update device debug functions Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 15/34] ml/cnxk: update device stats functions Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 16/34] ml/cnxk: update device and model xstats functions Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 17/34] ml/cnxk: update fast path functions Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 18/34] ml/cnxk: move error handling to cnxk layer Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 19/34] ml/cnxk: support config and close of tvmdp library Srikanth Yalavarthi
2023-09-21 12:32 ` Jerin Jacob
2023-09-27 18:38 ` [EXT] " Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 20/34] ml/cnxk: add structures to support TVM model type Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 21/34] ml/cnxk: add support for identify " Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 22/34] ml/cnxk: add support to parse TVM model objects Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 23/34] ml/cnxk: fetch layer info and load TVM model Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 24/34] ml/cnxk: update internal info for " Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 25/34] ml/cnxk: enable model unload in tvmdp library Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 26/34] ml/cnxk: support start and stop for TVM models Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 27/34] ml/cnxk: update internal TVM model info structure Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 28/34] ml/cnxk: support device dump for TVM models Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 29/34] ml/cnxk: enable reporting model runtime as xstats Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 30/34] ml/cnxk: implement I/O alloc and free callbacks Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 31/34] ml/cnxk: add generic ML malloc and free callback Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 32/34] ml/cnxk: support quantize and dequantize callback Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 33/34] ml/cnxk: enable fast-path ops for TVM models Srikanth Yalavarthi
2023-08-30 15:59 ` [PATCH v1 34/34] ml/cnxk: enable creation of mvtvm virtual device Srikanth Yalavarthi
2023-09-20 7:24 ` [PATCH v2 00/34] Implemenation of revised ml/cnxk driver Srikanth Yalavarthi
2023-09-20 7:24 ` [PATCH v2 01/34] ml/cnxk: drop support for register polling Srikanth Yalavarthi
2023-09-20 7:24 ` [PATCH v2 02/34] ml/cnxk: drop use of RTE API for firmware read Srikanth Yalavarthi
2023-09-20 7:24 ` [PATCH v2 03/34] ml/cnxk: add generic cnxk device structure Srikanth Yalavarthi
2023-09-20 7:24 ` [PATCH v2 04/34] ml/cnxk: add generic model and layer structures Srikanth Yalavarthi
2023-09-20 7:24 ` [PATCH v2 05/34] ml/cnxk: add generic cnxk request structure Srikanth Yalavarthi
2023-09-20 7:24 ` [PATCH v2 06/34] ml/cnxk: add generic cnxk xstats structures Srikanth Yalavarthi
2023-09-20 7:24 ` [PATCH v2 07/34] ml/cnxk: rename cnxk ops function pointers struct Srikanth Yalavarthi
2023-09-20 7:24 ` [PATCH v2 08/34] ml/cnxk: update device handling functions Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 09/34] ml/cnxk: update queue-pair " Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 10/34] ml/cnxk: update model load and unload functions Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 11/34] ml/cnxk: update model start and stop functions Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 12/34] ml/cnxk: update model utility functions Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 13/34] ml/cnxk: update data quantization functions Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 14/34] ml/cnxk: update device debug functions Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 15/34] ml/cnxk: update device stats functions Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 16/34] ml/cnxk: update device and model xstats functions Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 17/34] ml/cnxk: update fast path functions Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 18/34] ml/cnxk: move error handling to cnxk layer Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 19/34] ml/cnxk: support config and close of tvmdp library Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 20/34] ml/cnxk: add structures to support TVM model type Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 21/34] ml/cnxk: add support for identify " Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 22/34] ml/cnxk: add support to parse TVM model objects Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 23/34] ml/cnxk: fetch layer info and load TVM model Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 24/34] ml/cnxk: update internal info for " Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 25/34] ml/cnxk: enable model unload in tvmdp library Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 26/34] ml/cnxk: support start and stop for TVM models Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 27/34] ml/cnxk: update internal TVM model info structure Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 28/34] ml/cnxk: support device dump for TVM models Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 29/34] ml/cnxk: enable reporting model runtime as xstats Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 30/34] ml/cnxk: implement I/O alloc and free callbacks Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 31/34] ml/cnxk: add generic ML malloc and free callback Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 32/34] ml/cnxk: support quantize and dequantize callback Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 33/34] ml/cnxk: enable fast-path ops for TVM models Srikanth Yalavarthi
2023-09-20 7:25 ` [PATCH v2 34/34] ml/cnxk: enable creation of mvtvm virtual device Srikanth Yalavarthi
2023-09-21 12:15 ` [PATCH v2 00/34] Implemenation of revised ml/cnxk driver Jerin Jacob
2023-09-27 18:39 ` [EXT] " Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 00/35] " Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 01/35] ml/cnxk: drop support for register polling Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 02/35] ml/cnxk: add generic cnxk device structure Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 03/35] ml/cnxk: add generic model and layer structures Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 04/35] ml/cnxk: add generic cnxk request structure Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 05/35] ml/cnxk: add generic cnxk xstats structures Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 06/35] ml/cnxk: rename cnxk ops function pointers struct Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 07/35] ml/cnxk: update device handling functions Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 08/35] ml/cnxk: update queue-pair " Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 09/35] ml/cnxk: update model load and unload functions Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 10/35] ml/cnxk: update model start and stop functions Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 11/35] ml/cnxk: update model utility functions Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 12/35] ml/cnxk: update data quantization functions Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 13/35] ml/cnxk: update device debug functions Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 14/35] ml/cnxk: update device stats functions Srikanth Yalavarthi
2023-09-27 18:30 ` Srikanth Yalavarthi [this message]
2023-09-27 18:30 ` [PATCH v3 16/35] ml/cnxk: update fast path functions Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 17/35] ml/cnxk: move error handling to cnxk layer Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 18/35] ml/cnxk: support config and close of tvmdp library Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 19/35] ml/cnxk: add structures to support TVM model type Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 20/35] ml/cnxk: add support for identify " Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 21/35] ml/cnxk: add support to parse TVM model objects Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 22/35] ml/cnxk: fetch layer info and load TVM model Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 23/35] ml/cnxk: update internal info for " Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 24/35] ml/cnxk: enable model unload in tvmdp library Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 25/35] ml/cnxk: support start and stop for TVM models Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 26/35] ml/cnxk: update internal TVM model info structure Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 27/35] ml/cnxk: support device dump for TVM models Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 28/35] ml/cnxk: enable reporting model runtime as xstats Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 29/35] ml/cnxk: implement I/O alloc and free callbacks Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 30/35] ml/cnxk: add generic ML malloc and free callback Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 31/35] ml/cnxk: support quantize and dequantize callback Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 32/35] ml/cnxk: enable fast-path ops for TVM models Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 33/35] ml/cnxk: enable creation of mvtvm virtual device Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 34/35] ml/cnxk: update dependency info in driver docs Srikanth Yalavarthi
2023-09-28 4:12 ` Jerin Jacob
2023-10-01 0:32 ` [EXT] " Srikanth Yalavarthi
2023-10-17 17:03 ` Srikanth Yalavarthi
2023-09-27 18:30 ` [PATCH v3 35/35] ml/cnxk: update release notes for 23.11 Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 00/34] Implementation of revised ml/cnxk driver Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 01/34] ml/cnxk: drop support for register polling Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 02/34] ml/cnxk: add generic cnxk device structure Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 03/34] ml/cnxk: add generic model and layer structures Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 04/34] ml/cnxk: add generic cnxk request structure Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 05/34] ml/cnxk: add generic cnxk xstats structures Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 06/34] ml/cnxk: rename cnxk ops function pointers struct Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 07/34] ml/cnxk: update device handling functions Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 08/34] ml/cnxk: update queue-pair " Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 09/34] ml/cnxk: update model load and unload functions Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 10/34] ml/cnxk: enable OCM check for multilayer TVM model Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 11/34] ml/cnxk: update model start and stop functions Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 12/34] ml/cnxk: update model utility functions Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 13/34] ml/cnxk: update data quantization functions Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 14/34] ml/cnxk: update device debug functions Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 15/34] ml/cnxk: update device stats functions Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 16/34] ml/cnxk: update device and model xstats functions Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 17/34] ml/cnxk: update fast path functions Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 18/34] ml/cnxk: move error handling to cnxk layer Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 19/34] ml/cnxk: support config and close of tvmdp library Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 20/34] ml/cnxk: add structures to support TVM model type Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 21/34] ml/cnxk: add support for identify " Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 22/34] ml/cnxk: add support to parse TVM model objects Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 23/34] ml/cnxk: fetch layer info and load TVM model Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 24/34] ml/cnxk: update internal info for " Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 25/34] ml/cnxk: enable model unload in tvmdp library Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 26/34] ml/cnxk: support start and stop for TVM models Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 27/34] ml/cnxk: update internal TVM model info structure Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 28/34] ml/cnxk: support device dump for TVM models Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 29/34] ml/cnxk: enable reporting model runtime as xstats Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 30/34] ml/cnxk: implement I/O alloc and free callbacks Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 31/34] ml/cnxk: add generic ML malloc and free callback Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 32/34] ml/cnxk: support quantize and dequantize callback Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 33/34] ml/cnxk: enable fast-path ops for TVM models Srikanth Yalavarthi
2023-10-17 16:59 ` [PATCH v4 34/34] ml/cnxk: enable creation of mvtvm virtual device Srikanth Yalavarthi
2023-10-18 1:56 ` [PATCH v4 00/34] Implementation of revised ml/cnxk driver Jerin Jacob
2023-10-18 6:55 ` [EXT] " Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 " Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 01/34] ml/cnxk: drop support for register polling Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 02/34] ml/cnxk: add generic cnxk device structure Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 03/34] ml/cnxk: add generic model and layer structures Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 04/34] ml/cnxk: add generic cnxk request structure Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 05/34] ml/cnxk: add generic cnxk xstats structures Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 06/34] ml/cnxk: rename cnxk ops function pointers struct Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 07/34] ml/cnxk: update device handling functions Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 08/34] ml/cnxk: update queue-pair " Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 09/34] ml/cnxk: update model load and unload functions Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 10/34] ml/cnxk: update model start and stop functions Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 11/34] ml/cnxk: update model utility functions Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 12/34] ml/cnxk: update data quantization functions Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 13/34] ml/cnxk: update device debug functions Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 14/34] ml/cnxk: update device stats functions Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 15/34] ml/cnxk: update device and model xstats functions Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 16/34] ml/cnxk: update fast path functions Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 17/34] ml/cnxk: move error handling to cnxk layer Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 18/34] ml/cnxk: support config and close of tvmdp library Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 19/34] ml/cnxk: add structures to support TVM model type Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 20/34] ml/cnxk: add support for identify " Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 21/34] ml/cnxk: add support to parse TVM model objects Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 22/34] ml/cnxk: fetch layer info and load TVM model Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 23/34] ml/cnxk: update internal info for " Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 24/34] ml/cnxk: enable model unload in tvmdp library Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 25/34] ml/cnxk: enable OCM check for multilayer TVM model Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 26/34] ml/cnxk: support start and stop for TVM models Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 27/34] ml/cnxk: update internal TVM model info structure Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 28/34] ml/cnxk: support device dump for TVM models Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 29/34] ml/cnxk: enable reporting model runtime as xstats Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 30/34] ml/cnxk: implement I/O alloc and free callbacks Srikanth Yalavarthi
2023-10-18 6:47 ` [PATCH v5 31/34] ml/cnxk: add generic ML malloc and free callback Srikanth Yalavarthi
2023-10-18 6:48 ` [PATCH v5 32/34] ml/cnxk: support quantize and dequantize callback Srikanth Yalavarthi
2023-10-18 6:48 ` [PATCH v5 33/34] ml/cnxk: enable fast-path ops for TVM models Srikanth Yalavarthi
2023-10-18 6:48 ` [PATCH v5 34/34] ml/cnxk: enable creation of mvtvm virtual device Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 00/34] Implementation of revised ml/cnxk driver Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 01/34] ml/cnxk: drop support for register polling Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 02/34] ml/cnxk: add generic cnxk device structure Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 03/34] ml/cnxk: add generic model and layer structures Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 04/34] ml/cnxk: add generic cnxk request structure Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 05/34] ml/cnxk: add generic cnxk xstats structures Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 06/34] ml/cnxk: rename cnxk ops function pointers struct Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 07/34] ml/cnxk: update device handling functions Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 08/34] ml/cnxk: update queue-pair " Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 09/34] ml/cnxk: update model load and unload functions Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 10/34] ml/cnxk: update model start and stop functions Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 11/34] ml/cnxk: update model utility functions Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 12/34] ml/cnxk: update data quantization functions Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 13/34] ml/cnxk: update device debug functions Srikanth Yalavarthi
2023-10-18 13:53 ` [PATCH v6 14/34] ml/cnxk: update device stats functions Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 15/34] ml/cnxk: update device and model xstats functions Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 16/34] ml/cnxk: update fast path functions Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 17/34] ml/cnxk: move error handling to cnxk layer Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 18/34] ml/cnxk: support config and close of tvmdp library Srikanth Yalavarthi
2023-10-18 18:34 ` Jerin Jacob
2023-10-19 6:44 ` [EXT] " Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 19/34] ml/cnxk: add structures to support TVM model type Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 20/34] ml/cnxk: add support for identify " Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 21/34] ml/cnxk: add support to parse TVM model objects Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 22/34] ml/cnxk: fetch layer info and load TVM model Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 23/34] ml/cnxk: update internal info for " Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 24/34] ml/cnxk: enable model unload in tvmdp library Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 25/34] ml/cnxk: enable OCM check for multilayer TVM model Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 26/34] ml/cnxk: support start and stop for TVM models Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 27/34] ml/cnxk: update internal TVM model info structure Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 28/34] ml/cnxk: support device dump for TVM models Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 29/34] ml/cnxk: enable reporting model runtime as xstats Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 30/34] ml/cnxk: implement I/O alloc and free callbacks Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 31/34] ml/cnxk: add generic ML malloc and free callback Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 32/34] ml/cnxk: support quantize and dequantize callback Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 33/34] ml/cnxk: enable fast-path ops for TVM models Srikanth Yalavarthi
2023-10-18 13:54 ` [PATCH v6 34/34] ml/cnxk: enable creation of mvtvm virtual device Srikanth Yalavarthi
2023-10-18 14:20 ` [PATCH v6 00/34] Implementation of revised ml/cnxk driver Jerin Jacob
2023-10-19 6:41 ` [EXT] " Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 " Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 01/34] ml/cnxk: drop support for register polling Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 02/34] ml/cnxk: add generic cnxk device structure Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 03/34] ml/cnxk: add generic model and layer structures Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 04/34] ml/cnxk: add generic cnxk request structure Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 05/34] ml/cnxk: add generic cnxk xstats structures Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 06/34] ml/cnxk: rename cnxk ops function pointers struct Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 07/34] ml/cnxk: update device handling functions Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 08/34] ml/cnxk: update queue-pair " Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 09/34] ml/cnxk: update model load and unload functions Srikanth Yalavarthi
2023-10-19 4:16 ` [PATCH v7 10/34] ml/cnxk: update model start and stop functions Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 11/34] ml/cnxk: update model utility functions Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 12/34] ml/cnxk: update data quantization functions Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 13/34] ml/cnxk: update device debug functions Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 14/34] ml/cnxk: update device stats functions Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 15/34] ml/cnxk: update device and model xstats functions Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 16/34] ml/cnxk: update fast path functions Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 17/34] ml/cnxk: move error handling to cnxk layer Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 18/34] ml/cnxk: support config and close of tvmdp library Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 19/34] ml/cnxk: add structures to support TVM model type Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 20/34] ml/cnxk: add support for identify " Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 21/34] ml/cnxk: add support to parse TVM model objects Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 22/34] ml/cnxk: fetch layer info and load TVM model Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 23/34] ml/cnxk: update internal info for " Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 24/34] ml/cnxk: enable model unload in tvmdp library Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 25/34] ml/cnxk: enable OCM check for multilayer TVM model Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 26/34] ml/cnxk: support start and stop for TVM models Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 27/34] ml/cnxk: update internal TVM model info structure Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 28/34] ml/cnxk: support device dump for TVM models Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 29/34] ml/cnxk: enable reporting model runtime as xstats Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 30/34] ml/cnxk: implement I/O alloc and free callbacks Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 31/34] ml/cnxk: add generic ML malloc and free callback Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 32/34] ml/cnxk: support quantize and dequantize callback Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 33/34] ml/cnxk: enable fast-path ops for TVM models Srikanth Yalavarthi
2023-10-19 4:17 ` [PATCH v7 34/34] ml/cnxk: enable creation of mvtvm virtual device Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 00/34] Implementation of revised ml/cnxk driver Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 01/34] ml/cnxk: drop support for register polling Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 02/34] ml/cnxk: add generic cnxk device structure Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 03/34] ml/cnxk: add generic model and layer structures Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 04/34] ml/cnxk: add generic cnxk request structure Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 05/34] ml/cnxk: add generic cnxk xstats structures Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 06/34] ml/cnxk: rename cnxk ops function pointers struct Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 07/34] ml/cnxk: update device handling functions Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 08/34] ml/cnxk: update queue-pair " Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 09/34] ml/cnxk: update model load and unload functions Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 10/34] ml/cnxk: update model start and stop functions Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 11/34] ml/cnxk: update model utility functions Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 12/34] ml/cnxk: update data quantization functions Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 13/34] ml/cnxk: update device debug functions Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 14/34] ml/cnxk: update device stats functions Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 15/34] ml/cnxk: update device and model xstats functions Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 16/34] ml/cnxk: update fast path functions Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 17/34] ml/cnxk: move error handling to cnxk layer Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 18/34] ml/cnxk: support config and close of tvmdp library Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 19/34] ml/cnxk: add structures to support TVM model type Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 20/34] ml/cnxk: add support for identify " Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 21/34] ml/cnxk: add support to parse TVM model objects Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 22/34] ml/cnxk: fetch layer info and load TVM model Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 23/34] ml/cnxk: update internal info for " Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 24/34] ml/cnxk: enable model unload in tvmdp library Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 25/34] ml/cnxk: enable OCM check for multilayer TVM model Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 26/34] ml/cnxk: support start and stop for TVM models Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 27/34] ml/cnxk: update internal TVM model info structure Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 28/34] ml/cnxk: support device dump for TVM models Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 29/34] ml/cnxk: enable reporting model runtime as xstats Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 30/34] ml/cnxk: implement I/O alloc and free callbacks Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 31/34] ml/cnxk: add generic ML malloc and free callback Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 32/34] ml/cnxk: support quantize and dequantize callback Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 33/34] ml/cnxk: enable fast-path ops for TVM models Srikanth Yalavarthi
2023-10-23 4:41 ` [PATCH v8 34/34] ml/cnxk: enable creation of mvtvm virtual device Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 00/34] Implementation of revised ml/cnxk driver Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 01/34] ml/cnxk: drop support for register polling Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 02/34] ml/cnxk: add generic cnxk device structure Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 03/34] ml/cnxk: add generic model and layer structures Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 04/34] ml/cnxk: add generic cnxk request structure Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 05/34] ml/cnxk: add generic cnxk xstats structures Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 06/34] ml/cnxk: rename cnxk ops function pointers struct Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 07/34] ml/cnxk: update device handling functions Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 08/34] ml/cnxk: update queue-pair " Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 09/34] ml/cnxk: update model load and unload functions Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 10/34] ml/cnxk: update model start and stop functions Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 11/34] ml/cnxk: update model utility functions Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 12/34] ml/cnxk: update data quantization functions Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 13/34] ml/cnxk: update device debug functions Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 14/34] ml/cnxk: update device stats functions Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 15/34] ml/cnxk: update device and model xstats functions Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 16/34] ml/cnxk: update fast path functions Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 17/34] ml/cnxk: move error handling to cnxk layer Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 18/34] ml/cnxk: support config and close of tvmdp library Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 19/34] ml/cnxk: add structures to support TVM model type Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 20/34] ml/cnxk: add support for identify " Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 21/34] ml/cnxk: add support to parse TVM model objects Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 22/34] ml/cnxk: fetch layer info and load TVM model Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 23/34] ml/cnxk: update internal info for " Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 24/34] ml/cnxk: enable model unload in tvmdp library Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 25/34] ml/cnxk: enable OCM check for multilayer TVM model Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 26/34] ml/cnxk: support start and stop for TVM models Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 27/34] ml/cnxk: update internal TVM model info structure Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 28/34] ml/cnxk: support device dump for TVM models Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 29/34] ml/cnxk: enable reporting model runtime as xstats Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 30/34] ml/cnxk: implement I/O alloc and free callbacks Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 31/34] ml/cnxk: add generic ML malloc and free callback Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 32/34] ml/cnxk: support quantize and dequantize callback Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 33/34] ml/cnxk: enable fast-path ops for TVM models Srikanth Yalavarthi
2023-10-26 12:43 ` [PATCH v9 34/34] ml/cnxk: enable creation of mvtvm virtual device Srikanth Yalavarthi
2023-10-29 12:53 ` [PATCH v9 00/34] Implementation of revised ml/cnxk driver Jerin Jacob
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