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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 v9 29/34] ml/cnxk: enable reporting model runtime as xstats
Date: Thu, 26 Oct 2023 05:43:38 -0700	[thread overview]
Message-ID: <20231026124347.22477-30-syalavarthi@marvell.com> (raw)
In-Reply-To: <20231026124347.22477-1-syalavarthi@marvell.com>

Added model xstats entries to compute runtime latency.
Allocated internal resources for TVM model xstats.

Signed-off-by: Srikanth Yalavarthi <syalavarthi@marvell.com>
---
 drivers/ml/cnxk/cn10k_ml_ops.c   |   9 +++
 drivers/ml/cnxk/cn10k_ml_ops.h   |   2 +
 drivers/ml/cnxk/cnxk_ml_ops.c    | 131 +++++++++++++++++++++++++++----
 drivers/ml/cnxk/cnxk_ml_ops.h    |   1 +
 drivers/ml/cnxk/cnxk_ml_xstats.h |   7 ++
 drivers/ml/cnxk/mvtvm_ml_model.h |  24 ++++++
 drivers/ml/cnxk/mvtvm_ml_ops.c   |  96 +++++++++++++++++++++-
 drivers/ml/cnxk/mvtvm_ml_ops.h   |   8 ++
 drivers/ml/cnxk/mvtvm_ml_stubs.c |  23 ++++++
 drivers/ml/cnxk/mvtvm_ml_stubs.h |   6 ++
 10 files changed, 289 insertions(+), 18 deletions(-)

diff --git a/drivers/ml/cnxk/cn10k_ml_ops.c b/drivers/ml/cnxk/cn10k_ml_ops.c
index 2d308802cf..0c67ce7b40 100644
--- a/drivers/ml/cnxk/cn10k_ml_ops.c
+++ b/drivers/ml/cnxk/cn10k_ml_ops.c
@@ -197,6 +197,15 @@ cn10k_ml_xstats_layer_name_update(struct cnxk_ml_dev *cnxk_mldev, uint16_t model
 	}
 }
 
+void
+cn10k_ml_xstat_model_name_set(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model,
+			      uint16_t stat_id, uint16_t entry, char *suffix)
+{
+	snprintf(cnxk_mldev->xstats.entries[stat_id].map.name,
+		 sizeof(cnxk_mldev->xstats.entries[stat_id].map.name), "%s-%s-%s",
+		 model->glow.metadata.model.name, model_xstats[entry].name, suffix);
+}
+
 #define ML_AVG_FOREACH_QP(cnxk_mldev, layer, qp_id, str, value, count)                             \
 	do {                                                                                       \
 		value = 0;                                                                         \
diff --git a/drivers/ml/cnxk/cn10k_ml_ops.h b/drivers/ml/cnxk/cn10k_ml_ops.h
index 3d18303ed3..045e2e6cd2 100644
--- a/drivers/ml/cnxk/cn10k_ml_ops.h
+++ b/drivers/ml/cnxk/cn10k_ml_ops.h
@@ -331,6 +331,8 @@ 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 */
+void cn10k_ml_xstat_model_name_set(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model,
+				   uint16_t stat_id, uint16_t entry, char *suffix);
 uint64_t cn10k_ml_model_xstat_get(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_layer *layer,
 				  enum cnxk_ml_xstats_type type);
 
diff --git a/drivers/ml/cnxk/cnxk_ml_ops.c b/drivers/ml/cnxk/cnxk_ml_ops.c
index c38c60bf76..2632d70d8c 100644
--- a/drivers/ml/cnxk/cnxk_ml_ops.c
+++ b/drivers/ml/cnxk/cnxk_ml_ops.c
@@ -138,7 +138,8 @@ cnxk_ml_xstats_init(struct cnxk_ml_dev *cnxk_mldev)
 
 	/* 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;
+		   RTE_DIM(layer_xstats) * ML_CNXK_MAX_MODELS * ML_CNXK_MODEL_MAX_LAYERS +
+		   RTE_DIM(model_xstats) * ML_CNXK_MAX_MODELS;
 	if (cnxk_mldev->xstats.entries == NULL)
 		cnxk_mldev->xstats.entries = rte_zmalloc(
 			"cnxk_ml_xstats", sizeof(struct cnxk_ml_xstats_entry) * nb_stats,
@@ -169,6 +170,25 @@ cnxk_ml_xstats_init(struct cnxk_ml_dev *cnxk_mldev)
 	for (model = 0; model < ML_CNXK_MAX_MODELS; model++) {
 		cnxk_mldev->xstats.offset_for_model[model] = stat_id;
 
+		for (i = 0; i < RTE_DIM(model_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_MODEL;
+			cnxk_mldev->xstats.entries[stat_id].type = model_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 = -1;
+			cnxk_mldev->xstats.entries[stat_id].reset_allowed =
+				model_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),
+				 "Model-%u-%s", model, model_xstats[i].name);
+
+			stat_id++;
+		}
+
 		for (layer = 0; layer < ML_CNXK_MODEL_MAX_LAYERS; layer++) {
 			cnxk_mldev->xstats.offset_for_layer[model][layer] = stat_id;
 
@@ -195,7 +215,8 @@ cnxk_ml_xstats_init(struct cnxk_ml_dev *cnxk_mldev)
 			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_per_model[model] =
+			RTE_DIM(layer_xstats) + ML_CNXK_MODEL_MAX_LAYERS * RTE_DIM(model_xstats);
 	}
 
 	cnxk_mldev->xstats.count_mode_model = stat_id - cnxk_mldev->xstats.count_mode_device;
@@ -204,6 +225,36 @@ cnxk_ml_xstats_init(struct cnxk_ml_dev *cnxk_mldev)
 	return 0;
 }
 
+void
+cnxk_ml_xstats_model_name_update(struct cnxk_ml_dev *cnxk_mldev, uint16_t model_id)
+{
+	struct cnxk_ml_model *model;
+	uint16_t rclk_freq;
+	uint16_t sclk_freq;
+	uint16_t stat_id;
+	char suffix[8];
+	uint16_t i;
+
+	model = cnxk_mldev->mldev->data->models[model_id];
+	stat_id = cnxk_mldev->xstats.offset_for_model[model_id];
+
+	roc_clk_freq_get(&rclk_freq, &sclk_freq);
+	if (sclk_freq == 0)
+		rte_strscpy(suffix, "cycles", 7);
+	else
+		rte_strscpy(suffix, "ns", 3);
+
+	/* Update xstat name based on layer name and sclk availability */
+	for (i = 0; i < RTE_DIM(model_xstats); i++) {
+		if (model->type == ML_CNXK_MODEL_TYPE_GLOW)
+			cn10k_ml_xstat_model_name_set(cnxk_mldev, model, stat_id, i, suffix);
+		else
+			mvtvm_ml_model_xstat_name_set(cnxk_mldev, model, stat_id, i, suffix);
+
+		stat_id++;
+	}
+}
+
 static void
 cnxk_ml_xstats_uninit(struct cnxk_ml_dev *cnxk_mldev)
 {
@@ -247,13 +298,22 @@ cnxk_ml_model_xstat_get(struct cnxk_ml_dev *cnxk_mldev, uint16_t obj_idx, int32_
 	if (model == NULL)
 		return 0;
 
-	if (layer_id >= 0)
+	if (layer_id >= 0) {
 		layer = &model->layer[layer_id];
-	else
-		return 0;
+		goto layer_xstats;
+	} else {
+		layer = NULL;
+		goto model_xstats;
+	}
 
+layer_xstats:
 	value = cn10k_ml_model_xstat_get(cnxk_mldev, layer, type);
+	goto exit_xstats;
 
+model_xstats:
+	value = mvtvm_ml_model_xstat_get(cnxk_mldev, model, type);
+
+exit_xstats:
 	roc_clk_freq_get(&rclk_freq, &sclk_freq);
 	if (sclk_freq != 0) /* return in ns */
 		value = (value * 1000ULL) / sclk_freq;
@@ -836,8 +896,9 @@ cnxk_ml_dev_xstats_names_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode
 {
 	struct cnxk_ml_xstats_entry *xs;
 	struct cnxk_ml_dev *cnxk_mldev;
+	struct cnxk_ml_model *model;
 	uint32_t xstats_mode_count;
-	uint16_t layer_id = 0;
+	uint16_t layer_id;
 	uint32_t idx = 0;
 	uint32_t i;
 
@@ -854,7 +915,17 @@ cnxk_ml_dev_xstats_names_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode
 	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];
+
+		model = cnxk_mldev->mldev->data->models[model_id];
+		for (layer_id = 0; layer_id < model->nb_layers; layer_id++) {
+			if (model->layer[layer_id].type == ML_CNXK_LAYER_TYPE_MRVL)
+				xstats_mode_count +=
+					cnxk_mldev->xstats.count_per_layer[model_id][layer_id];
+		}
+
+		if ((model->type == ML_CNXK_MODEL_TYPE_TVM) &&
+		    (model->subtype != ML_CNXK_MODEL_SUBTYPE_TVM_MRVL))
+			xstats_mode_count += RTE_DIM(model_xstats);
 		break;
 	default:
 		return -EINVAL;
@@ -868,9 +939,20 @@ cnxk_ml_dev_xstats_names_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode
 		if (xs->mode != mode)
 			continue;
 
-		if (mode == RTE_ML_DEV_XSTATS_MODEL &&
-		    (model_id != xs->obj_idx || layer_id != xs->layer_id))
-			continue;
+		if (mode == RTE_ML_DEV_XSTATS_MODEL) {
+			if (model_id != xs->obj_idx)
+				continue;
+
+			model = cnxk_mldev->mldev->data->models[model_id];
+			if ((model->type == ML_CNXK_MODEL_TYPE_GLOW ||
+			     model->subtype == ML_CNXK_MODEL_SUBTYPE_TVM_MRVL) &&
+			    xs->group == CNXK_ML_XSTATS_GROUP_MODEL)
+				continue;
+
+			if (model->type == ML_CNXK_MODEL_TYPE_TVM &&
+			    model->layer[xs->layer_id].type == ML_CNXK_LAYER_TYPE_LLVM)
+				continue;
+		}
 
 		rte_strscpy(xstats_map[idx].name, xs->map.name, RTE_ML_STR_MAX);
 		xstats_map[idx].id = xs->map.id;
@@ -931,9 +1013,10 @@ cnxk_ml_dev_xstats_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode,
 {
 	struct cnxk_ml_xstats_entry *xs;
 	struct cnxk_ml_dev *cnxk_mldev;
+	struct cnxk_ml_model *model;
 	uint32_t xstats_mode_count;
-	uint16_t layer_id = 0;
 	cnxk_ml_xstats_fn fn;
+	uint16_t layer_id;
 	uint64_t val;
 	uint32_t idx;
 	uint32_t i;
@@ -951,7 +1034,14 @@ cnxk_ml_dev_xstats_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode,
 	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];
+
+		model = cnxk_mldev->mldev->data->models[model_id];
+		for (layer_id = 0; layer_id < model->nb_layers; layer_id++)
+			xstats_mode_count += cnxk_mldev->xstats.count_per_layer[model_id][layer_id];
+
+		if ((model->type == ML_CNXK_MODEL_TYPE_TVM) &&
+		    (model->subtype != ML_CNXK_MODEL_SUBTYPE_TVM_MRVL))
+			xstats_mode_count += RTE_DIM(model_xstats);
 		break;
 	default:
 		return -EINVAL;
@@ -963,11 +1053,18 @@ cnxk_ml_dev_xstats_get(struct rte_ml_dev *dev, enum rte_ml_dev_xstats_mode mode,
 		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;
+		if (mode == RTE_ML_DEV_XSTATS_MODEL) {
+			if (model_id != xs->obj_idx)
+				continue;
+
+			model = cnxk_mldev->mldev->data->models[xs->obj_idx];
+			if ((model->type == ML_CNXK_MODEL_TYPE_GLOW ||
+			     model->subtype == ML_CNXK_MODEL_SUBTYPE_TVM_MRVL) &&
+			    xs->group == CNXK_ML_XSTATS_GROUP_MODEL)
+				continue;
+
+			if (xs->layer_id == -1 && xs->group == CNXK_ML_XSTATS_GROUP_LAYER)
+				continue;
 		}
 
 		switch (xs->fn_id) {
diff --git a/drivers/ml/cnxk/cnxk_ml_ops.h b/drivers/ml/cnxk/cnxk_ml_ops.h
index b22a2b0d95..ab32676b3e 100644
--- a/drivers/ml/cnxk/cnxk_ml_ops.h
+++ b/drivers/ml/cnxk/cnxk_ml_ops.h
@@ -70,6 +70,7 @@ 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);
+void cnxk_ml_xstats_model_name_update(struct cnxk_ml_dev *cnxk_mldev, uint16_t model_id);
 
 __rte_hot uint16_t cnxk_ml_enqueue_burst(struct rte_ml_dev *dev, uint16_t qp_id,
 					 struct rte_ml_op **ops, uint16_t nb_ops);
diff --git a/drivers/ml/cnxk/cnxk_ml_xstats.h b/drivers/ml/cnxk/cnxk_ml_xstats.h
index 5e02bb876c..a2c9adfe4a 100644
--- a/drivers/ml/cnxk/cnxk_ml_xstats.h
+++ b/drivers/ml/cnxk/cnxk_ml_xstats.h
@@ -142,4 +142,11 @@ static const struct cnxk_ml_xstat_info layer_xstats[] = {
 	{"Min-FW-Latency", min_fw_latency, 1}, {"Max-FW-Latency", max_fw_latency, 1},
 };
 
+/* Model xstats */
+static const struct cnxk_ml_xstat_info model_xstats[] = {
+	{"Avg-RT-Latency", avg_rt_latency, 1},
+	{"Min-RT-Latency", min_rt_latency, 1},
+	{"Max-RT-Latency", max_rt_latency, 1},
+};
+
 #endif /* _CNXK_ML_XSTATS_H_ */
diff --git a/drivers/ml/cnxk/mvtvm_ml_model.h b/drivers/ml/cnxk/mvtvm_ml_model.h
index 900ba44fa0..66c3af18e1 100644
--- a/drivers/ml/cnxk/mvtvm_ml_model.h
+++ b/drivers/ml/cnxk/mvtvm_ml_model.h
@@ -33,6 +33,27 @@ struct mvtvm_ml_model_object {
 	int64_t size;
 };
 
+/* Model fast-path stats */
+struct mvtvm_ml_model_xstats {
+	/* Total TVM runtime latency, sum of all inferences */
+	uint64_t tvm_rt_latency_tot;
+
+	/* TVM runtime latency */
+	uint64_t tvm_rt_latency;
+
+	/* Minimum TVM runtime latency */
+	uint64_t tvm_rt_latency_min;
+
+	/* Maximum TVM runtime latency */
+	uint64_t tvm_rt_latency_max;
+
+	/* Total jobs dequeued */
+	uint64_t dequeued_count;
+
+	/* Hardware stats reset index */
+	uint64_t tvm_rt_reset_count;
+};
+
 struct mvtvm_ml_model_data {
 	/* Model metadata */
 	struct tvmdp_model_metadata metadata;
@@ -45,6 +66,9 @@ struct mvtvm_ml_model_data {
 
 	/* Model I/O info */
 	struct cnxk_ml_io_info info;
+
+	/* Stats for burst ops */
+	struct mvtvm_ml_model_xstats *burst_xstats;
 };
 
 enum cnxk_ml_model_type mvtvm_ml_model_type_get(struct rte_ml_model_params *params);
diff --git a/drivers/ml/cnxk/mvtvm_ml_ops.c b/drivers/ml/cnxk/mvtvm_ml_ops.c
index c6872cd89a..abfbae2b3a 100644
--- a/drivers/ml/cnxk/mvtvm_ml_ops.c
+++ b/drivers/ml/cnxk/mvtvm_ml_ops.c
@@ -10,10 +10,83 @@
 #include "cnxk_ml_dev.h"
 #include "cnxk_ml_model.h"
 #include "cnxk_ml_ops.h"
+#include "cnxk_ml_xstats.h"
 
 /* ML model macros */
 #define MVTVM_ML_MODEL_MEMZONE_NAME "ml_mvtvm_model_mz"
 
+void
+mvtvm_ml_model_xstat_name_set(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model,
+			      uint16_t stat_id, uint16_t entry, char *suffix)
+{
+	snprintf(cnxk_mldev->xstats.entries[stat_id].map.name,
+		 sizeof(cnxk_mldev->xstats.entries[stat_id].map.name), "%s-%s-%s",
+		 model->mvtvm.metadata.model.name, model_xstats[entry].name, suffix);
+}
+
+#define ML_AVG_FOREACH_QP_MVTVM(cnxk_mldev, model, qp_id, value, count)                            \
+	do {                                                                                       \
+		value = 0;                                                                         \
+		for (qp_id = 0; qp_id < cnxk_mldev->mldev->data->nb_queue_pairs; qp_id++) {        \
+			value += model->mvtvm.burst_xstats[qp_id].tvm_rt_latency_tot;              \
+			count += model->mvtvm.burst_xstats[qp_id].dequeued_count -                 \
+				 model->mvtvm.burst_xstats[qp_id].tvm_rt_reset_count;              \
+		}                                                                                  \
+		if (count != 0)                                                                    \
+			value = value / count;                                                     \
+	} while (0)
+
+#define ML_MIN_FOREACH_QP_MVTVM(cnxk_mldev, model, qp_id, value, count)                            \
+	do {                                                                                       \
+		value = UINT64_MAX;                                                                \
+		for (qp_id = 0; qp_id < cnxk_mldev->mldev->data->nb_queue_pairs; qp_id++) {        \
+			value = PLT_MIN(value,                                                     \
+					model->mvtvm.burst_xstats[qp_id].tvm_rt_latency_min);      \
+			count += model->mvtvm.burst_xstats[qp_id].dequeued_count -                 \
+				 model->mvtvm.burst_xstats[qp_id].tvm_rt_reset_count;              \
+		}                                                                                  \
+		if (count == 0)                                                                    \
+			value = 0;                                                                 \
+	} while (0)
+
+#define ML_MAX_FOREACH_QP_MVTVM(cnxk_mldev, model, qp_id, value, count)                            \
+	do {                                                                                       \
+		value = 0;                                                                         \
+		for (qp_id = 0; qp_id < cnxk_mldev->mldev->data->nb_queue_pairs; qp_id++) {        \
+			value = PLT_MAX(value,                                                     \
+					model->mvtvm.burst_xstats[qp_id].tvm_rt_latency_max);      \
+			count += model->mvtvm.burst_xstats[qp_id].dequeued_count -                 \
+				 model->mvtvm.burst_xstats[qp_id].tvm_rt_reset_count;              \
+		}                                                                                  \
+		if (count == 0)                                                                    \
+			value = 0;                                                                 \
+	} while (0)
+
+uint64_t
+mvtvm_ml_model_xstat_get(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model,
+			 enum cnxk_ml_xstats_type type)
+{
+	uint64_t count = 0;
+	uint64_t value = 0;
+	uint32_t qp_id;
+
+	switch (type) {
+	case avg_rt_latency:
+		ML_AVG_FOREACH_QP_MVTVM(cnxk_mldev, model, qp_id, value, count);
+		break;
+	case min_rt_latency:
+		ML_MIN_FOREACH_QP_MVTVM(cnxk_mldev, model, qp_id, value, count);
+		break;
+	case max_rt_latency:
+		ML_MAX_FOREACH_QP_MVTVM(cnxk_mldev, model, qp_id, value, count);
+		break;
+	default:
+		value = 0;
+	}
+
+	return value;
+}
+
 int
 mvtvm_ml_dev_configure(struct cnxk_ml_dev *cnxk_mldev, const struct rte_ml_dev_config *conf)
 {
@@ -53,6 +126,7 @@ mvtvm_ml_model_load(struct cnxk_ml_dev *cnxk_mldev, struct rte_ml_model_params *
 	char str[RTE_MEMZONE_NAMESIZE];
 	const struct plt_memzone *mz;
 	size_t model_object_size = 0;
+	size_t model_xstats_size = 0;
 	uint16_t nb_mrvl_layers;
 	uint16_t nb_llvm_layers;
 	uint8_t layer_id = 0;
@@ -68,7 +142,11 @@ mvtvm_ml_model_load(struct cnxk_ml_dev *cnxk_mldev, struct rte_ml_model_params *
 	model_object_size = RTE_ALIGN_CEIL(object[0].size, RTE_CACHE_LINE_MIN_SIZE) +
 			    RTE_ALIGN_CEIL(object[1].size, RTE_CACHE_LINE_MIN_SIZE) +
 			    RTE_ALIGN_CEIL(object[2].size, RTE_CACHE_LINE_MIN_SIZE);
-	mz_size += model_object_size;
+
+	model_xstats_size =
+		cnxk_mldev->mldev->data->nb_queue_pairs * sizeof(struct mvtvm_ml_model_xstats);
+
+	mz_size += model_object_size + model_xstats_size;
 
 	/* Allocate memzone for model object */
 	snprintf(str, RTE_MEMZONE_NAMESIZE, "%s_%u", MVTVM_ML_MODEL_MEMZONE_NAME, model->model_id);
@@ -181,6 +259,22 @@ mvtvm_ml_model_load(struct cnxk_ml_dev *cnxk_mldev, struct rte_ml_model_params *
 	/* Set model info */
 	mvtvm_ml_model_info_set(cnxk_mldev, model);
 
+	/* Update model xstats name */
+	cnxk_ml_xstats_model_name_update(cnxk_mldev, model->model_id);
+
+	model->mvtvm.burst_xstats = RTE_PTR_ADD(
+		model->mvtvm.object.params.addr,
+		RTE_ALIGN_CEIL(model->mvtvm.object.params.size, RTE_CACHE_LINE_MIN_SIZE));
+
+	for (int qp_id = 0; qp_id < cnxk_mldev->mldev->data->nb_queue_pairs; qp_id++) {
+		model->mvtvm.burst_xstats[qp_id].tvm_rt_latency_tot = 0;
+		model->mvtvm.burst_xstats[qp_id].tvm_rt_latency = 0;
+		model->mvtvm.burst_xstats[qp_id].tvm_rt_latency_min = UINT64_MAX;
+		model->mvtvm.burst_xstats[qp_id].tvm_rt_latency_max = 0;
+		model->mvtvm.burst_xstats[qp_id].tvm_rt_reset_count = 0;
+		model->mvtvm.burst_xstats[qp_id].dequeued_count = 0;
+	}
+
 	return 0;
 
 error:
diff --git a/drivers/ml/cnxk/mvtvm_ml_ops.h b/drivers/ml/cnxk/mvtvm_ml_ops.h
index 55459f9f7f..22e0340146 100644
--- a/drivers/ml/cnxk/mvtvm_ml_ops.h
+++ b/drivers/ml/cnxk/mvtvm_ml_ops.h
@@ -11,8 +11,11 @@
 
 #include <rte_mldev.h>
 
+#include "cnxk_ml_xstats.h"
+
 struct cnxk_ml_dev;
 struct cnxk_ml_model;
+struct cnxk_ml_layer;
 
 int mvtvm_ml_dev_configure(struct cnxk_ml_dev *cnxk_mldev, const struct rte_ml_dev_config *conf);
 int mvtvm_ml_dev_close(struct cnxk_ml_dev *cnxk_mldev);
@@ -22,4 +25,9 @@ int mvtvm_ml_model_unload(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *
 int mvtvm_ml_model_start(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model);
 int mvtvm_ml_model_stop(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model);
 
+void mvtvm_ml_model_xstat_name_set(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model,
+				   uint16_t stat_id, uint16_t entry, char *suffix);
+uint64_t mvtvm_ml_model_xstat_get(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model,
+				  enum cnxk_ml_xstats_type type);
+
 #endif /* _MVTVM_ML_OPS_H_ */
diff --git a/drivers/ml/cnxk/mvtvm_ml_stubs.c b/drivers/ml/cnxk/mvtvm_ml_stubs.c
index 260a051b08..19af1d2703 100644
--- a/drivers/ml/cnxk/mvtvm_ml_stubs.c
+++ b/drivers/ml/cnxk/mvtvm_ml_stubs.c
@@ -8,6 +8,7 @@
 
 #include "cnxk_ml_dev.h"
 #include "cnxk_ml_model.h"
+#include "cnxk_ml_xstats.h"
 
 enum cnxk_ml_model_type
 mvtvm_ml_model_type_get(struct rte_ml_model_params *params)
@@ -44,6 +45,28 @@ mvtvm_ml_layer_print(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_layer *layer
 	RTE_SET_USED(fp);
 }
 
+void
+mvtvm_ml_model_xstat_name_set(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model,
+			      uint16_t stat_id, uint16_t entry, char *suffix)
+{
+	RTE_SET_USED(cnxk_mldev);
+	RTE_SET_USED(model);
+	RTE_SET_USED(stat_id);
+	RTE_SET_USED(entry);
+	RTE_SET_USED(suffix);
+}
+
+uint64_t
+mvtvm_ml_model_xstat_get(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model,
+			 enum cnxk_ml_xstats_type type)
+{
+	RTE_SET_USED(cnxk_mldev);
+	RTE_SET_USED(model);
+	RTE_SET_USED(type);
+
+	return 0;
+}
+
 int
 mvtvm_ml_dev_configure(struct cnxk_ml_dev *cnxk_mldev, const struct rte_ml_dev_config *conf)
 {
diff --git a/drivers/ml/cnxk/mvtvm_ml_stubs.h b/drivers/ml/cnxk/mvtvm_ml_stubs.h
index d6d0edbcf1..3fd1f04c35 100644
--- a/drivers/ml/cnxk/mvtvm_ml_stubs.h
+++ b/drivers/ml/cnxk/mvtvm_ml_stubs.h
@@ -7,6 +7,8 @@
 
 #include <rte_mldev.h>
 
+#include "cnxk_ml_xstats.h"
+
 struct cnxk_ml_dev;
 struct cnxk_ml_model;
 struct cnxk_ml_layer;
@@ -24,5 +26,9 @@ int mvtvm_ml_model_get_layer_id(struct cnxk_ml_model *model, const char *layer_n
 				uint16_t *layer_id);
 struct cnxk_ml_io_info *mvtvm_ml_model_io_info_get(struct cnxk_ml_model *model, uint16_t layer_id);
 void mvtvm_ml_layer_print(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_layer *layer, FILE *fp);
+void mvtvm_ml_model_xstat_name_set(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model,
+				   uint16_t stat_id, uint16_t entry, char *suffix);
+uint64_t mvtvm_ml_model_xstat_get(struct cnxk_ml_dev *cnxk_mldev, struct cnxk_ml_model *model,
+				  enum cnxk_ml_xstats_type type);
 
 #endif /* _MVTVM_ML_STUBS_H_ */
-- 
2.42.0


  parent reply	other threads:[~2023-10-26 12:48 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   ` [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   ` Srikanth Yalavarthi [this message]
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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