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 v1 11/34] ml/cnxk: update model start and stop functions
Date: Wed, 30 Aug 2023 08:59:01 -0700 [thread overview]
Message-ID: <20230830155927.3566-12-syalavarthi@marvell.com> (raw)
In-Reply-To: <20230830155927.3566-1-syalavarthi@marvell.com>
Implemented cnxk wrapper functions to start and stop
ML models. Wrapper functions would invoke the cn10k
model start and stop functions.
Signed-off-by: Srikanth Yalavarthi <syalavarthi@marvell.com>
---
drivers/ml/cnxk/cn10k_ml_ocm.c | 28 ++--
drivers/ml/cnxk/cn10k_ml_ocm.h | 12 +-
drivers/ml/cnxk/cn10k_ml_ops.c | 282 ++++++++++++++++++++-------------
drivers/ml/cnxk/cn10k_ml_ops.h | 8 +-
drivers/ml/cnxk/cnxk_ml_ops.c | 48 +++++-
drivers/ml/cnxk/cnxk_ml_ops.h | 1 +
6 files changed, 240 insertions(+), 139 deletions(-)
diff --git a/drivers/ml/cnxk/cn10k_ml_ocm.c b/drivers/ml/cnxk/cn10k_ml_ocm.c
index 639f329f8aa..6a8400b7763 100644
--- a/drivers/ml/cnxk/cn10k_ml_ocm.c
+++ b/drivers/ml/cnxk/cn10k_ml_ocm.c
@@ -217,11 +217,10 @@ cn10k_ml_ocm_tilecount(uint64_t tilemask, int *start, int *end)
* scratch & WB pages and OCM allocation mode.
*/
int
-cn10k_ml_ocm_tilemask_find(struct rte_ml_dev *dev, uint8_t num_tiles, uint16_t wb_pages,
+cn10k_ml_ocm_tilemask_find(struct cnxk_ml_dev *cnxk_mldev, uint8_t num_tiles, uint16_t wb_pages,
uint16_t scratch_pages, uint64_t *tilemask)
{
struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_dev *cnxk_mldev;
struct cn10k_ml_ocm *ocm;
uint16_t used_scratch_pages_max;
@@ -240,7 +239,6 @@ cn10k_ml_ocm_tilemask_find(struct rte_ml_dev *dev, uint8_t num_tiles, uint16_t w
int max_slot_sz;
int page_id;
- cnxk_mldev = dev->data->dev_private;
cn10k_mldev = &cnxk_mldev->cn10k_mldev;
ocm = &cn10k_mldev->ocm;
@@ -335,12 +333,10 @@ cn10k_ml_ocm_tilemask_find(struct rte_ml_dev *dev, uint8_t num_tiles, uint16_t w
}
void
-cn10k_ml_ocm_reserve_pages(struct rte_ml_dev *dev, uint16_t model_id, uint16_t layer_id,
+cn10k_ml_ocm_reserve_pages(struct cnxk_ml_dev *cnxk_mldev, uint16_t model_id, uint16_t layer_id,
uint64_t tilemask, int wb_page_start, uint16_t wb_pages,
uint16_t scratch_pages)
{
- struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_dev *cnxk_mldev;
struct cnxk_ml_model *model;
struct cnxk_ml_layer *layer;
struct cn10k_ml_ocm *ocm;
@@ -353,10 +349,8 @@ cn10k_ml_ocm_reserve_pages(struct rte_ml_dev *dev, uint16_t model_id, uint16_t l
int tile_id;
int page_id;
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
- ocm = &cn10k_mldev->ocm;
- model = dev->data->models[model_id];
+ ocm = &cnxk_mldev->cn10k_mldev.ocm;
+ model = cnxk_mldev->mldev->data->models[model_id];
layer = &model->layer[layer_id];
/* Get first set bit, tile_start */
@@ -398,12 +392,10 @@ cn10k_ml_ocm_reserve_pages(struct rte_ml_dev *dev, uint16_t model_id, uint16_t l
}
void
-cn10k_ml_ocm_free_pages(struct rte_ml_dev *dev, uint16_t model_id, uint16_t layer_id)
+cn10k_ml_ocm_free_pages(struct cnxk_ml_dev *cnxk_mldev, uint16_t model_id, uint16_t layer_id)
{
struct cnxk_ml_model *local_model;
struct cnxk_ml_layer *local_layer;
- struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_dev *cnxk_mldev;
struct cnxk_ml_model *model;
struct cnxk_ml_layer *layer;
struct cn10k_ml_ocm *ocm;
@@ -418,10 +410,8 @@ cn10k_ml_ocm_free_pages(struct rte_ml_dev *dev, uint16_t model_id, uint16_t laye
uint16_t i;
uint16_t j;
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
- ocm = &cn10k_mldev->ocm;
- model = dev->data->models[model_id];
+ ocm = &cnxk_mldev->cn10k_mldev.ocm;
+ model = cnxk_mldev->mldev->data->models[model_id];
layer = &model->layer[layer_id];
/* Update OCM info for WB memory */
@@ -440,8 +430,8 @@ cn10k_ml_ocm_free_pages(struct rte_ml_dev *dev, uint16_t model_id, uint16_t laye
/* Get max scratch pages required, excluding the current model */
scratch_resize_pages = 0;
- for (i = 0; i < dev->data->nb_models; i++) {
- local_model = dev->data->models[i];
+ for (i = 0; i < cnxk_mldev->mldev->data->nb_models; i++) {
+ local_model = cnxk_mldev->mldev->data->models[i];
if (local_model == NULL)
continue;
diff --git a/drivers/ml/cnxk/cn10k_ml_ocm.h b/drivers/ml/cnxk/cn10k_ml_ocm.h
index 720f8caf766..97b723a56a5 100644
--- a/drivers/ml/cnxk/cn10k_ml_ocm.h
+++ b/drivers/ml/cnxk/cn10k_ml_ocm.h
@@ -8,6 +8,8 @@
#include <rte_mldev.h>
#include <rte_mldev_pmd.h>
+struct cnxk_ml_dev;
+
/* Number of OCM tiles. */
#define ML_CN10K_OCM_NUMTILES 0x8
@@ -75,12 +77,12 @@ struct cn10k_ml_ocm {
};
int cn10k_ml_ocm_tilecount(uint64_t tilemask, int *start, int *end);
-int cn10k_ml_ocm_tilemask_find(struct rte_ml_dev *dev, uint8_t num_tiles, uint16_t wb_pages,
+int cn10k_ml_ocm_tilemask_find(struct cnxk_ml_dev *cnxk_mldev, uint8_t num_tiles, uint16_t wb_pages,
uint16_t scratch_pages, uint64_t *tilemask);
-void cn10k_ml_ocm_reserve_pages(struct rte_ml_dev *dev, uint16_t model_id, uint16_t layer_id,
- uint64_t tilemask, int wb_page_start, uint16_t wb_pages,
- uint16_t scratch_pages);
-void cn10k_ml_ocm_free_pages(struct rte_ml_dev *dev, uint16_t model_id, uint16_t layer_id);
+void cn10k_ml_ocm_reserve_pages(struct cnxk_ml_dev *cnxk_mldev, uint16_t model_id,
+ uint16_t layer_id, uint64_t tilemask, int wb_page_start,
+ uint16_t wb_pages, uint16_t scratch_pages);
+void cn10k_ml_ocm_free_pages(struct cnxk_ml_dev *cnxk_mldev, uint16_t model_id, uint16_t layer_id);
void cn10k_ml_ocm_print(struct rte_ml_dev *dev, FILE *fp);
#endif /* _CN10K_ML_OCM_H_ */
diff --git a/drivers/ml/cnxk/cn10k_ml_ops.c b/drivers/ml/cnxk/cn10k_ml_ops.c
index 3bfc63d9d40..e5b9837ed73 100644
--- a/drivers/ml/cnxk/cn10k_ml_ops.c
+++ b/drivers/ml/cnxk/cn10k_ml_ops.c
@@ -252,26 +252,28 @@ cn10k_ml_model_print(struct rte_ml_dev *dev, uint16_t model_id, FILE *fp)
}
static void
-cn10k_ml_prep_sp_job_descriptor(struct cn10k_ml_dev *cn10k_mldev, struct cnxk_ml_model *model,
+cn10k_ml_prep_sp_job_descriptor(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_layer *layer,
struct cnxk_ml_req *req, enum cn10k_ml_job_type job_type)
{
struct cn10k_ml_model_metadata *metadata;
struct cn10k_ml_layer_addr *addr;
+ struct cn10k_ml_dev *cn10k_mldev;
- metadata = &model->glow.metadata;
- addr = &model->layer[0].glow.addr;
+ cn10k_mldev = &cnxk_mldev->cn10k_mldev;
+ metadata = &layer->glow.metadata;
+ addr = &layer->glow.addr;
memset(&req->cn10k_req.jd, 0, sizeof(struct cn10k_ml_jd));
req->cn10k_req.jd.hdr.jce.w0.u64 = 0;
req->cn10k_req.jd.hdr.jce.w1.u64 = PLT_U64_CAST(&req->cn10k_req.status);
- req->cn10k_req.jd.hdr.model_id = model->model_id;
+ req->cn10k_req.jd.hdr.model_id = layer->index;
req->cn10k_req.jd.hdr.job_type = job_type;
req->cn10k_req.jd.hdr.fp_flags = 0x0;
req->cn10k_req.jd.hdr.result =
roc_ml_addr_ap2mlip(&cn10k_mldev->roc, &req->cn10k_req.result);
if (job_type == ML_CN10K_JOB_TYPE_MODEL_START) {
- if (!model->glow.metadata.model.ocm_relocatable)
+ if (!layer->glow.metadata.model.ocm_relocatable)
req->cn10k_req.jd.hdr.sp_flags = ML_CN10K_SP_FLAGS_OCM_NONRELOCATABLE;
else
req->cn10k_req.jd.hdr.sp_flags = 0x0;
@@ -295,7 +297,7 @@ cn10k_ml_prep_sp_job_descriptor(struct cn10k_ml_dev *cn10k_mldev, struct cnxk_ml
req->cn10k_req.jd.model_start.num_gather_entries = 0;
req->cn10k_req.jd.model_start.num_scatter_entries = 0;
req->cn10k_req.jd.model_start.tilemask = 0; /* Updated after reserving pages */
- req->cn10k_req.jd.model_start.batch_size = model->batch_size;
+ req->cn10k_req.jd.model_start.batch_size = layer->batch_size;
req->cn10k_req.jd.model_start.ocm_wb_base_address =
0; /* Updated after reserving pages */
req->cn10k_req.jd.model_start.ocm_wb_range_start =
@@ -327,9 +329,13 @@ cn10k_ml_prep_sp_job_descriptor(struct cn10k_ml_dev *cn10k_mldev, struct cnxk_ml
}
static __rte_always_inline void
-cn10k_ml_prep_fp_job_descriptor(struct cn10k_ml_dev *cn10k_mldev, struct cnxk_ml_req *req,
+cn10k_ml_prep_fp_job_descriptor(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_req *req,
struct rte_ml_op *op)
{
+ struct cn10k_ml_dev *cn10k_mldev;
+
+ cn10k_mldev = &cnxk_mldev->cn10k_mldev;
+
req->cn10k_req.jd.hdr.jce.w0.u64 = 0;
req->cn10k_req.jd.hdr.jce.w1.u64 = PLT_U64_CAST(req->status);
req->cn10k_req.jd.hdr.model_id = op->model_id;
@@ -718,10 +724,8 @@ cn10k_ml_model_xstats_reset(struct rte_ml_dev *dev, int32_t model_id, const uint
}
static int
-cn10k_ml_cache_model_data(struct rte_ml_dev *dev, uint16_t model_id)
+cn10k_ml_cache_model_data(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_layer *layer)
{
- struct rte_ml_model_info *info;
- struct cnxk_ml_model *model;
struct rte_ml_buff_seg seg[2];
struct rte_ml_buff_seg *inp;
struct rte_ml_buff_seg *out;
@@ -734,22 +738,20 @@ cn10k_ml_cache_model_data(struct rte_ml_dev *dev, uint16_t model_id)
int ret = 0;
uint32_t i;
- model = dev->data->models[model_id];
- info = (struct rte_ml_model_info *)model->info;
inp = &seg[0];
out = &seg[1];
/* Create input and output buffers. */
- for (i = 0; i < info->nb_inputs; i++)
- isize += info->input_info[i].size;
+ for (i = 0; i < layer->info.nb_inputs; i++)
+ isize += layer->info.input[i].sz_q;
- for (i = 0; i < info->nb_outputs; i++)
- osize += info->output_info[i].size;
+ for (i = 0; i < layer->info.nb_outputs; i++)
+ osize += layer->info.output[i].sz_q;
- isize = model->batch_size * isize;
- osize = model->batch_size * osize;
+ isize = layer->batch_size * isize;
+ osize = layer->batch_size * osize;
- snprintf(str, RTE_MEMZONE_NAMESIZE, "%s_%u", "ml_dummy_io", model_id);
+ snprintf(str, RTE_MEMZONE_NAMESIZE, "%s_%u", "ml_dummy_io", layer->index);
mz = plt_memzone_reserve_aligned(str, isize + osize, 0, ML_CN10K_ALIGN_SIZE);
if (mz == NULL)
return -ENOMEM;
@@ -765,15 +767,15 @@ cn10k_ml_cache_model_data(struct rte_ml_dev *dev, uint16_t model_id)
seg[1].length = osize;
seg[1].next = NULL;
- op.model_id = model_id;
- op.nb_batches = model->batch_size;
+ op.model_id = layer->index;
+ op.nb_batches = layer->batch_size;
op.mempool = NULL;
op.input = &inp;
op.output = &out;
- memset(model->layer[0].glow.req, 0, sizeof(struct cnxk_ml_req));
- ret = cn10k_ml_inference_sync(dev, &op);
+ memset(layer->glow.req, 0, sizeof(struct cnxk_ml_req));
+ ret = cn10k_ml_inference_sync(cnxk_mldev, &op);
plt_memzone_free(mz);
return ret;
@@ -1510,14 +1512,16 @@ cn10k_ml_model_unload(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *mode
}
int
-cn10k_ml_model_start(struct rte_ml_dev *dev, uint16_t model_id)
+cn10k_ml_layer_start(void *device, uint16_t model_id, const char *layer_name)
{
struct cn10k_ml_dev *cn10k_mldev;
struct cnxk_ml_dev *cnxk_mldev;
struct cnxk_ml_model *model;
+ struct cnxk_ml_layer *layer;
struct cn10k_ml_ocm *ocm;
struct cnxk_ml_req *req;
+ uint16_t layer_id = 0;
bool job_enqueued;
bool job_dequeued;
uint8_t num_tiles;
@@ -1528,85 +1532,89 @@ cn10k_ml_model_start(struct rte_ml_dev *dev, uint16_t model_id)
bool locked;
int ret = 0;
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
- ocm = &cn10k_mldev->ocm;
- model = dev->data->models[model_id];
+ PLT_SET_USED(layer_name);
+ cnxk_mldev = (struct cnxk_ml_dev *)device;
+ if (cnxk_mldev == NULL) {
+ plt_err("Invalid device = %p", device);
+ return -EINVAL;
+ }
+
+ model = cnxk_mldev->mldev->data->models[model_id];
if (model == NULL) {
plt_err("Invalid model_id = %u", model_id);
return -EINVAL;
}
+ layer = &model->layer[layer_id];
+ cn10k_mldev = &cnxk_mldev->cn10k_mldev;
+ ocm = &cn10k_mldev->ocm;
+
/* Prepare JD */
- req = model->layer[0].glow.req;
- cn10k_ml_prep_sp_job_descriptor(cn10k_mldev, model, req, ML_CN10K_JOB_TYPE_MODEL_START);
+ req = layer->glow.req;
+ cn10k_ml_prep_sp_job_descriptor(cnxk_mldev, layer, req, ML_CN10K_JOB_TYPE_MODEL_START);
req->cn10k_req.result.error_code = 0x0;
req->cn10k_req.result.user_ptr = NULL;
plt_write64(ML_CNXK_POLL_JOB_START, &req->cn10k_req.status);
plt_wmb();
- num_tiles = model->layer[0].glow.metadata.model.tile_end -
- model->layer[0].glow.metadata.model.tile_start + 1;
+ num_tiles = layer->glow.metadata.model.tile_end - layer->glow.metadata.model.tile_start + 1;
locked = false;
while (!locked) {
if (plt_spinlock_trylock(&model->lock) != 0) {
- if (model->state == ML_CNXK_MODEL_STATE_STARTED) {
- plt_ml_dbg("Model already started, model = 0x%016lx",
- PLT_U64_CAST(model));
+ if (layer->state == ML_CNXK_LAYER_STATE_STARTED) {
+ plt_ml_dbg("Layer already started, model_id = %u, layer_id = %u",
+ model->model_id, layer_id);
plt_spinlock_unlock(&model->lock);
return 1;
}
- if (model->state == ML_CNXK_MODEL_STATE_JOB_ACTIVE) {
- plt_err("A slow-path job is active for the model = 0x%016lx",
- PLT_U64_CAST(model));
+ if (layer->state == ML_CNXK_LAYER_STATE_JOB_ACTIVE) {
+ plt_err("A slow-path job is active for the model_id = %u",
+ model->model_id);
plt_spinlock_unlock(&model->lock);
return -EBUSY;
}
- model->state = ML_CNXK_MODEL_STATE_JOB_ACTIVE;
+ layer->state = ML_CNXK_LAYER_STATE_JOB_ACTIVE;
plt_spinlock_unlock(&model->lock);
locked = true;
}
}
- while (!model->layer[0].glow.ocm_map.ocm_reserved) {
+ while (!layer->glow.ocm_map.ocm_reserved) {
if (plt_spinlock_trylock(&ocm->lock) != 0) {
wb_page_start = cn10k_ml_ocm_tilemask_find(
- dev, num_tiles, model->layer[0].glow.ocm_map.wb_pages,
- model->layer[0].glow.ocm_map.scratch_pages, &tilemask);
+ cnxk_mldev, num_tiles, layer->glow.ocm_map.wb_pages,
+ layer->glow.ocm_map.scratch_pages, &tilemask);
if (wb_page_start == -1) {
plt_err("Free pages not available on OCM tiles");
- plt_err("Failed to start model = 0x%016lx, name = %s",
- PLT_U64_CAST(model),
- model->layer[0].glow.metadata.model.name);
-
+ plt_err("Failed to start layer, model_id = %u, layer_id = %u",
+ model->model_id, layer_id);
plt_spinlock_unlock(&ocm->lock);
return -ENOMEM;
}
- model->layer[0].glow.ocm_map.tilemask = tilemask;
- model->layer[0].glow.ocm_map.wb_page_start = wb_page_start;
+ layer->glow.ocm_map.tilemask = tilemask;
+ layer->glow.ocm_map.wb_page_start = wb_page_start;
- cn10k_ml_ocm_reserve_pages(dev, model->model_id, 0,
- model->layer[0].glow.ocm_map.tilemask,
- model->layer[0].glow.ocm_map.wb_page_start,
- model->layer[0].glow.ocm_map.wb_pages,
- model->layer[0].glow.ocm_map.scratch_pages);
- model->layer[0].glow.ocm_map.ocm_reserved = true;
+ cn10k_ml_ocm_reserve_pages(
+ cnxk_mldev, model->model_id, layer_id, layer->glow.ocm_map.tilemask,
+ layer->glow.ocm_map.wb_page_start, layer->glow.ocm_map.wb_pages,
+ layer->glow.ocm_map.scratch_pages);
+ layer->glow.ocm_map.ocm_reserved = true;
plt_spinlock_unlock(&ocm->lock);
}
}
/* Update JD */
- cn10k_ml_ocm_tilecount(model->layer[0].glow.ocm_map.tilemask, &tile_start, &tile_end);
+ cn10k_ml_ocm_tilecount(layer->glow.ocm_map.tilemask, &tile_start, &tile_end);
req->cn10k_req.jd.model_start.tilemask = GENMASK_ULL(tile_end, tile_start);
req->cn10k_req.jd.model_start.ocm_wb_base_address =
- model->layer[0].glow.ocm_map.wb_page_start * ocm->page_size;
+ layer->glow.ocm_map.wb_page_start * ocm->page_size;
job_enqueued = false;
job_dequeued = false;
@@ -1640,66 +1648,94 @@ cn10k_ml_model_start(struct rte_ml_dev *dev, uint16_t model_id)
locked = false;
while (!locked) {
if (plt_spinlock_trylock(&model->lock) != 0) {
- if (ret == 0) {
- model->state = ML_CNXK_MODEL_STATE_STARTED;
- cnxk_mldev->nb_models_started++;
- } else {
- model->state = ML_CNXK_MODEL_STATE_UNKNOWN;
- }
+ if (ret == 0)
+ layer->state = ML_CNXK_LAYER_STATE_STARTED;
+ else
+ layer->state = ML_CNXK_LAYER_STATE_UNKNOWN;
plt_spinlock_unlock(&model->lock);
locked = true;
}
}
- if (model->state == ML_CNXK_MODEL_STATE_UNKNOWN) {
- while (model->layer[0].glow.ocm_map.ocm_reserved) {
+ if (layer->state == ML_CNXK_LAYER_STATE_UNKNOWN) {
+ while (layer->glow.ocm_map.ocm_reserved) {
if (plt_spinlock_trylock(&ocm->lock) != 0) {
- cn10k_ml_ocm_free_pages(dev, model->model_id, 0);
- model->layer[0].glow.ocm_map.ocm_reserved = false;
- model->layer[0].glow.ocm_map.tilemask = 0x0;
+ cn10k_ml_ocm_free_pages(cnxk_mldev, model->model_id, layer_id);
+ layer->glow.ocm_map.ocm_reserved = false;
+ layer->glow.ocm_map.tilemask = 0x0;
plt_spinlock_unlock(&ocm->lock);
}
}
}
- if (ret < 0) { /* Call unload to update model and FW state, ignore error */
- rte_ml_model_stop(dev->data->dev_id, model_id);
+ if (ret < 0) {
+ cn10k_ml_layer_stop(device, model_id, layer_name);
} else {
- if (cn10k_mldev->cache_model_data && roc_model_is_cn10ka())
- ret = cn10k_ml_cache_model_data(dev, model_id);
+ if (cn10k_mldev->cache_model_data)
+ ret = cn10k_ml_cache_model_data(cnxk_mldev, layer);
}
return ret;
}
int
-cn10k_ml_model_stop(struct rte_ml_dev *dev, uint16_t model_id)
+cn10k_ml_model_start(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model)
+{
+ struct cnxk_ml_layer *layer;
+ int ret;
+
+ layer = &model->layer[0];
+ ret = cn10k_ml_layer_start(cnxk_mldev, model->model_id, layer->name);
+ if (ret != 0) {
+ plt_err("CN10K Model start failed, model_id = %u, error = %d", model->model_id,
+ ret);
+ return ret;
+ }
+
+ cnxk_mldev->nb_models_started++;
+ model->state = ML_CNXK_MODEL_STATE_STARTED;
+
+ return 0;
+}
+
+int
+cn10k_ml_layer_stop(void *device, uint16_t model_id, const char *layer_name)
{
struct cn10k_ml_dev *cn10k_mldev;
struct cnxk_ml_dev *cnxk_mldev;
struct cnxk_ml_model *model;
+ struct cnxk_ml_layer *layer;
struct cn10k_ml_ocm *ocm;
struct cnxk_ml_req *req;
+ uint16_t layer_id = 0;
bool job_enqueued;
bool job_dequeued;
bool locked;
int ret = 0;
- cnxk_mldev = dev->data->dev_private;
- cn10k_mldev = &cnxk_mldev->cn10k_mldev;
- ocm = &cn10k_mldev->ocm;
- model = dev->data->models[model_id];
+ PLT_SET_USED(layer_name);
+
+ cnxk_mldev = (struct cnxk_ml_dev *)device;
+ if (cnxk_mldev == NULL) {
+ plt_err("Invalid device = %p", device);
+ return -EINVAL;
+ }
+ model = cnxk_mldev->mldev->data->models[model_id];
if (model == NULL) {
plt_err("Invalid model_id = %u", model_id);
return -EINVAL;
}
+ layer = &model->layer[layer_id];
+ cn10k_mldev = &cnxk_mldev->cn10k_mldev;
+ ocm = &cn10k_mldev->ocm;
+
/* Prepare JD */
- req = model->layer[0].glow.req;
- cn10k_ml_prep_sp_job_descriptor(cn10k_mldev, model, req, ML_CN10K_JOB_TYPE_MODEL_STOP);
+ req = layer->glow.req;
+ cn10k_ml_prep_sp_job_descriptor(cnxk_mldev, layer, req, ML_CN10K_JOB_TYPE_MODEL_STOP);
req->cn10k_req.result.error_code = 0x0;
req->cn10k_req.result.user_ptr = NULL;
@@ -1709,31 +1745,31 @@ cn10k_ml_model_stop(struct rte_ml_dev *dev, uint16_t model_id)
locked = false;
while (!locked) {
if (plt_spinlock_trylock(&model->lock) != 0) {
- if (model->state == ML_CNXK_MODEL_STATE_LOADED) {
- plt_ml_dbg("Model not started, model = 0x%016lx",
- PLT_U64_CAST(model));
+ if (layer->state == ML_CNXK_LAYER_STATE_LOADED) {
+ plt_ml_dbg("Layer not started, model_id = %u, layer_id = %u",
+ model->model_id, layer_id);
plt_spinlock_unlock(&model->lock);
return 1;
}
- if (model->state == ML_CNXK_MODEL_STATE_JOB_ACTIVE) {
- plt_err("A slow-path job is active for the model = 0x%016lx",
- PLT_U64_CAST(model));
+ if (layer->state == ML_CNXK_LAYER_STATE_JOB_ACTIVE) {
+ plt_err("A slow-path job is active for the layer, model_id = %u, layer_id = %u",
+ model->model_id, layer_id);
plt_spinlock_unlock(&model->lock);
return -EBUSY;
}
- model->state = ML_CNXK_MODEL_STATE_JOB_ACTIVE;
+ layer->state = ML_CNXK_LAYER_STATE_JOB_ACTIVE;
plt_spinlock_unlock(&model->lock);
locked = true;
}
}
- while (model->layer[0].glow.ocm_map.ocm_reserved) {
+ while (layer->glow.ocm_map.ocm_reserved) {
if (plt_spinlock_trylock(&ocm->lock) != 0) {
- cn10k_ml_ocm_free_pages(dev, model->model_id, 0);
- model->layer[0].glow.ocm_map.ocm_reserved = false;
- model->layer[0].glow.ocm_map.tilemask = 0x0;
+ cn10k_ml_ocm_free_pages(cnxk_mldev, model->model_id, layer_id);
+ layer->glow.ocm_map.ocm_reserved = false;
+ layer->glow.ocm_map.tilemask = 0x0;
plt_spinlock_unlock(&ocm->lock);
}
}
@@ -1770,8 +1806,11 @@ cn10k_ml_model_stop(struct rte_ml_dev *dev, uint16_t model_id)
locked = false;
while (!locked) {
if (plt_spinlock_trylock(&model->lock) != 0) {
- cnxk_mldev->nb_models_stopped++;
- model->state = ML_CNXK_MODEL_STATE_LOADED;
+ if (ret == 0)
+ layer->state = ML_CNXK_LAYER_STATE_LOADED;
+ else
+ layer->state = ML_CNXK_LAYER_STATE_UNKNOWN;
+
plt_spinlock_unlock(&model->lock);
locked = true;
}
@@ -1780,6 +1819,25 @@ cn10k_ml_model_stop(struct rte_ml_dev *dev, uint16_t model_id)
return ret;
}
+int
+cn10k_ml_model_stop(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model)
+{
+ struct cnxk_ml_layer *layer;
+ int ret;
+
+ layer = &model->layer[0];
+ ret = cn10k_ml_layer_stop(cnxk_mldev, model->model_id, layer->name);
+ if (ret != 0) {
+ plt_err("CN10K Model stop failed, model_id = %u, error = %d", model->model_id, ret);
+ return ret;
+ }
+
+ cnxk_mldev->nb_models_stopped++;
+ model->state = ML_CNXK_MODEL_STATE_LOADED;
+
+ return 0;
+}
+
int
cn10k_ml_model_info_get(struct rte_ml_dev *dev, uint16_t model_id,
struct rte_ml_model_info *model_info)
@@ -2007,30 +2065,35 @@ queue_free_count(uint64_t head, uint64_t tail, uint64_t nb_desc)
}
static __rte_always_inline void
-cn10k_ml_result_update(struct rte_ml_dev *dev, int qp_id, struct cnxk_ml_req *req)
+cn10k_ml_result_update(struct cnxk_ml_dev *cnxk_mldev, int qp_id, struct cnxk_ml_req *req)
{
union cn10k_ml_error_code *error_code;
struct cn10k_ml_layer_xstats *xstats;
struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_dev *cnxk_mldev;
struct cn10k_ml_result *result;
struct cnxk_ml_model *model;
+ struct cnxk_ml_layer *layer;
struct cnxk_ml_qp *qp;
struct rte_ml_op *op;
uint64_t hw_latency;
uint64_t fw_latency;
+ uint16_t model_id;
+ uint16_t layer_id;
result = &req->cn10k_req.result;
op = req->op;
if (likely(result->error_code == 0)) {
- model = dev->data->models[op->model_id];
+ model_id = cnxk_mldev->index_map[op->model_id].model_id;
+ layer_id = cnxk_mldev->index_map[op->model_id].layer_id;
+ model = cnxk_mldev->mldev->data->models[model_id];
+ layer = &model->layer[layer_id];
if (likely(qp_id >= 0)) {
- qp = dev->data->queue_pairs[qp_id];
+ qp = cnxk_mldev->mldev->data->queue_pairs[qp_id];
qp->stats.dequeued_count++;
- xstats = &model->layer[0].glow.burst_xstats[qp_id];
+ xstats = &layer->glow.burst_xstats[qp_id];
} else {
- xstats = model->layer[0].glow.sync_xstats;
+ xstats = layer->glow.sync_xstats;
}
if (unlikely(xstats->dequeued_count == xstats->hw_reset_count)) {
@@ -2058,14 +2121,13 @@ cn10k_ml_result_update(struct rte_ml_dev *dev, int qp_id, struct cnxk_ml_req *re
op->status = RTE_ML_OP_STATUS_SUCCESS;
} else {
if (likely(qp_id >= 0)) {
- qp = dev->data->queue_pairs[qp_id];
+ qp = cnxk_mldev->mldev->data->queue_pairs[qp_id];
qp->stats.dequeue_err_count++;
}
/* Handle driver error */
error_code = (union cn10k_ml_error_code *)&result->error_code;
if (error_code->s.etype == ML_ETYPE_DRIVER) {
- cnxk_mldev = dev->data->dev_private;
cn10k_mldev = &cnxk_mldev->cn10k_mldev;
/* Check for exception */
@@ -2120,7 +2182,7 @@ cn10k_ml_enqueue_burst(struct rte_ml_dev *dev, uint16_t qp_id, struct rte_ml_op
req = &queue->reqs[head];
cn10k_mldev->set_poll_addr(req);
- cn10k_ml_prep_fp_job_descriptor(cn10k_mldev, req, op);
+ cn10k_ml_prep_fp_job_descriptor(cnxk_mldev, req, op);
memset(&req->cn10k_req.result, 0, sizeof(struct cn10k_ml_result));
error_code = (union cn10k_ml_error_code *)&req->cn10k_req.result.error_code;
@@ -2187,7 +2249,7 @@ cn10k_ml_dequeue_burst(struct rte_ml_dev *dev, uint16_t qp_id, struct rte_ml_op
}
}
- cn10k_ml_result_update(dev, qp_id, req);
+ cn10k_ml_result_update(cnxk_mldev, qp_id, req);
ops[count] = req->op;
queue_index_advance(&tail, qp->nb_desc);
@@ -2236,23 +2298,27 @@ cn10k_ml_op_error_get(struct rte_ml_dev *dev, struct rte_ml_op *op, struct rte_m
}
__rte_hot int
-cn10k_ml_inference_sync(struct rte_ml_dev *dev, struct rte_ml_op *op)
+cn10k_ml_inference_sync(struct cnxk_ml_dev *cnxk_mldev, struct rte_ml_op *op)
{
union cn10k_ml_error_code *error_code;
struct cn10k_ml_dev *cn10k_mldev;
- struct cnxk_ml_dev *cnxk_mldev;
struct cnxk_ml_model *model;
+ struct cnxk_ml_layer *layer;
struct cnxk_ml_req *req;
+ uint16_t model_id;
+ uint16_t layer_id;
bool timeout;
int ret = 0;
- cnxk_mldev = dev->data->dev_private;
cn10k_mldev = &cnxk_mldev->cn10k_mldev;
- model = dev->data->models[op->model_id];
- req = model->layer[0].glow.req;
+ model_id = cnxk_mldev->index_map[op->model_id].model_id;
+ layer_id = cnxk_mldev->index_map[op->model_id].layer_id;
+ model = cnxk_mldev->mldev->data->models[model_id];
+ layer = &model->layer[layer_id];
+ req = layer->glow.req;
cn10k_ml_set_poll_addr(req);
- cn10k_ml_prep_fp_job_descriptor(cn10k_mldev, req, op);
+ cn10k_ml_prep_fp_job_descriptor(cnxk_mldev, req, op);
memset(&req->cn10k_req.result, 0, sizeof(struct cn10k_ml_result));
error_code = (union cn10k_ml_error_code *)&req->cn10k_req.result.error_code;
@@ -2288,7 +2354,7 @@ cn10k_ml_inference_sync(struct rte_ml_dev *dev, struct rte_ml_op *op)
if (timeout)
ret = -ETIME;
else
- cn10k_ml_result_update(dev, -1, req);
+ cn10k_ml_result_update(cnxk_mldev, -1, req);
error_enqueue:
return ret;
diff --git a/drivers/ml/cnxk/cn10k_ml_ops.h b/drivers/ml/cnxk/cn10k_ml_ops.h
index 677219dfdf7..a222a43d552 100644
--- a/drivers/ml/cnxk/cn10k_ml_ops.h
+++ b/drivers/ml/cnxk/cn10k_ml_ops.h
@@ -315,8 +315,8 @@ int cn10k_ml_dev_xstats_reset(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mod
int cn10k_ml_model_load(struct cnxk_ml_dev *cnxk_mldev, struct rte_ml_model_params *params,
struct cnxk_ml_model *model);
int cn10k_ml_model_unload(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model);
-int cn10k_ml_model_start(struct rte_ml_dev *dev, uint16_t model_id);
-int cn10k_ml_model_stop(struct rte_ml_dev *dev, uint16_t model_id);
+int cn10k_ml_model_start(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model);
+int cn10k_ml_model_stop(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model);
int cn10k_ml_model_info_get(struct rte_ml_dev *dev, uint16_t model_id,
struct rte_ml_model_info *model_info);
int cn10k_ml_model_params_update(struct rte_ml_dev *dev, uint16_t model_id, void *buffer);
@@ -335,7 +335,7 @@ __rte_hot uint16_t cn10k_ml_dequeue_burst(struct rte_ml_dev *dev, uint16_t qp_id
struct rte_ml_op **ops, uint16_t nb_ops);
__rte_hot int cn10k_ml_op_error_get(struct rte_ml_dev *dev, struct rte_ml_op *op,
struct rte_ml_op_error *error);
-__rte_hot int cn10k_ml_inference_sync(struct rte_ml_dev *dev, struct rte_ml_op *op);
+__rte_hot int cn10k_ml_inference_sync(struct cnxk_ml_dev *cnxk_mldev, struct rte_ml_op *op);
/* Misc ops */
void cn10k_ml_qp_initialize(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_qp *qp);
@@ -344,5 +344,7 @@ void cn10k_ml_qp_initialize(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_qp *q
int cn10k_ml_layer_load(void *device, uint16_t model_id, const char *layer_name, uint8_t *buffer,
size_t size, uint16_t *index);
int cn10k_ml_layer_unload(void *device, uint16_t model_id, const char *layer_name);
+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);
#endif /* _CN10K_ML_OPS_H_ */
diff --git a/drivers/ml/cnxk/cnxk_ml_ops.c b/drivers/ml/cnxk/cnxk_ml_ops.c
index 3d9d5f9d78c..915309168d8 100644
--- a/drivers/ml/cnxk/cnxk_ml_ops.c
+++ b/drivers/ml/cnxk/cnxk_ml_ops.c
@@ -242,7 +242,7 @@ cnxk_ml_dev_configure(struct rte_ml_dev *dev, const struct rte_ml_dev_config *co
model = dev->data->models[model_id];
if (model != NULL) {
if (model->state == ML_CNXK_MODEL_STATE_STARTED) {
- if (cn10k_ml_model_stop(dev, model_id) != 0)
+ if (cnxk_ml_model_stop(dev, model_id) != 0)
plt_err("Could not stop model %u", model_id);
}
if (model->state == ML_CNXK_MODEL_STATE_LOADED) {
@@ -334,7 +334,7 @@ cnxk_ml_dev_close(struct rte_ml_dev *dev)
model = dev->data->models[model_id];
if (model != NULL) {
if (model->state == ML_CNXK_MODEL_STATE_STARTED) {
- if (cn10k_ml_model_stop(dev, model_id) != 0)
+ if (cnxk_ml_model_stop(dev, model_id) != 0)
plt_err("Could not stop model %u", model_id);
}
if (model->state == ML_CNXK_MODEL_STATE_LOADED) {
@@ -566,6 +566,46 @@ cnxk_ml_model_unload(struct rte_ml_dev *dev, uint16_t model_id)
return plt_memzone_free(plt_memzone_lookup(str));
}
+static int
+cnxk_ml_model_start(struct rte_ml_dev *dev, uint16_t model_id)
+{
+ struct cnxk_ml_dev *cnxk_mldev;
+ struct cnxk_ml_model *model;
+
+ if (dev == NULL)
+ return -EINVAL;
+
+ cnxk_mldev = dev->data->dev_private;
+
+ model = dev->data->models[model_id];
+ if (model == NULL) {
+ plt_err("Invalid model_id = %u", model_id);
+ return -EINVAL;
+ }
+
+ return cn10k_ml_model_start(cnxk_mldev, model);
+}
+
+int
+cnxk_ml_model_stop(struct rte_ml_dev *dev, uint16_t model_id)
+{
+ struct cnxk_ml_dev *cnxk_mldev;
+ struct cnxk_ml_model *model;
+
+ if (dev == NULL)
+ return -EINVAL;
+
+ cnxk_mldev = dev->data->dev_private;
+
+ model = dev->data->models[model_id];
+ if (model == NULL) {
+ plt_err("Invalid model_id = %u", model_id);
+ return -EINVAL;
+ }
+
+ return cn10k_ml_model_stop(cnxk_mldev, model);
+}
+
struct rte_ml_dev_ops cnxk_ml_ops = {
/* Device control ops */
.dev_info_get = cnxk_ml_dev_info_get,
@@ -591,8 +631,8 @@ struct rte_ml_dev_ops cnxk_ml_ops = {
/* Model ops */
.model_load = cnxk_ml_model_load,
.model_unload = cnxk_ml_model_unload,
- .model_start = cn10k_ml_model_start,
- .model_stop = cn10k_ml_model_stop,
+ .model_start = cnxk_ml_model_start,
+ .model_stop = cnxk_ml_model_stop,
.model_info_get = cn10k_ml_model_info_get,
.model_params_update = cn10k_ml_model_params_update,
diff --git a/drivers/ml/cnxk/cnxk_ml_ops.h b/drivers/ml/cnxk/cnxk_ml_ops.h
index bc14f6e5b9e..d27ca0d0cb2 100644
--- a/drivers/ml/cnxk/cnxk_ml_ops.h
+++ b/drivers/ml/cnxk/cnxk_ml_ops.h
@@ -63,5 +63,6 @@ struct cnxk_ml_qp {
extern struct rte_ml_dev_ops cnxk_ml_ops;
int cnxk_ml_model_unload(struct rte_ml_dev *dev, uint16_t model_id);
+int cnxk_ml_model_stop(struct rte_ml_dev *dev, uint16_t model_id);
#endif /* _CNXK_ML_OPS_H_ */
--
2.41.0
next prev parent reply other threads:[~2023-08-30 16:01 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 ` Srikanth Yalavarthi [this message]
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 ` [PATCH v3 15/35] ml/cnxk: update device and model xstats functions Srikanth Yalavarthi
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
Reply instructions:
You may reply publicly to this message via plain-text email
using any one of the following methods:
* Save the following mbox file, import it into your mail client,
and reply-to-all from there: mbox
Avoid top-posting and favor interleaved quoting:
https://en.wikipedia.org/wiki/Posting_style#Interleaved_style
* Reply using the --to, --cc, and --in-reply-to
switches of git-send-email(1):
git send-email \
--in-reply-to=20230830155927.3566-12-syalavarthi@marvell.com \
--to=syalavarthi@marvell.com \
--cc=aprabhu@marvell.com \
--cc=dev@dpdk.org \
--cc=ptakkar@marvell.com \
--cc=sshankarnara@marvell.com \
/path/to/YOUR_REPLY
https://kernel.org/pub/software/scm/git/docs/git-send-email.html
* If your mail client supports setting the In-Reply-To header
via mailto: links, try the mailto: link
Be sure your reply has a Subject: header at the top and a blank line
before the message body.
This is a public inbox, see mirroring instructions
for how to clone and mirror all data and code used for this inbox;
as well as URLs for NNTP newsgroup(s).