new file mode 100644
@@ -0,0 +1,91 @@
+.. SPDX-License-Identifier: BSD-3-Clause
+ Copyright (c) 2021 NVIDIA Corporation & Affiliates
+
+CUDA GPU driver
+===============
+
+The CUDA GPU driver library (**librte_gpu_cuda**) provides support for NVIDIA GPUs.
+Information and documentation about these devices can be found on the
+`NVIDIA website <http://www.nvidia.com>`__. Help is also provided by the
+`NVIDIA CUDA Toolkit developer zone <https://docs.nvidia.com/cuda>`__.
+
+Design
+------
+
+**librte_gpu_cuda** relies on CUDA Driver API (no need for CUDA Runtime API).
+
+Goal of this driver library is not to provide a wrapper for the whole CUDA Driver API.
+Instead, the scope is to implement the generic features of gpudev API.
+For a CUDA application, integrating the gpudev library functions using the CUDA driver library
+is quite straighforward and doesn't create any compatibility problem.
+
+Initialization
+~~~~~~~~~~~~~~
+
+During initialization, CUDA driver library detects NVIDIA physical GPUs on the
+system or specified via EAL device options (e.g. ``-a b6:00.0``).
+The driver initializes the CUDA driver environment through ``cuInit(0)`` function.
+For this reason, it's required to set any CUDA environment configuration before
+calling ``rte_eal_init`` function in the DPDK application.
+
+If the CUDA driver enviroment has been already initialized, the ``cuInit(0)``
+in CUDA driver library has no effect.
+
+CUDA Driver sub-contexts
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+After initialization, a CUDA application can create multiple sub-contexts on GPU
+physical devices. Through gpudev library, is possible to register these sub-contexts
+in the CUDA driver library as child devices having as parent a GPU physical device.
+
+CUDA driver library also supports `MPS <https://docs.nvidia.com/deploy/pdf/CUDA_Multi_Process_Service_Overview.pdf>`__.
+
+GPU memory management
+~~~~~~~~~~~~~~~~~~~~~
+
+The CUDA driver library maintains a table of GPU memory addresses allocated
+and CPU memory addresses registered associated to the input CUDA context.
+Whenever the application tried to deallocate or deregister a memory address,
+if the address is not in the table the CUDA driver library will return an error.
+
+Features
+--------
+
+- Register new child devices aka new CUDA Driver contexts
+- Allocate memory on the GPU
+- Register CPU memory to make it visible from GPU
+
+Minimal requirements
+--------------------
+
+Minimal requirements to enable the CUDA driver library are:
+
+- NVIDIA GPU Ampere or Volta
+- CUDA 11.4 Driver API or newer
+
+`GPUDirect RDMA Technology <https://docs.nvidia.com/cuda/gpudirect-rdma/index.html>`__
+allows compatible network cards (e.g. Mellanox) to directly send and receive packets
+using GPU memory instead of additional memory copies through the CPU system memory.
+To enable this technology, system requirements are:
+
+- `nvidia-peermem <https://docs.nvidia.com/cuda/gpudirect-rdma/index.html#nvidia-peermem>`__ module running on the system
+- Mellanox Network card ConnectX-5 or newer (BlueField models included)
+- DPDK mlx5 PMD enabled
+- To reach the best performance, a PCIe switch between GPU and NIC is recommended
+
+Limitations
+-----------
+
+Supported only on Linux.
+
+Supported GPUs
+--------------
+
+The following NVIDIA GPU devices are supported by this CUDA driver:
+
+- NVIDIA A100 80GB PCIe
+- NVIDIA A100 40GB PCIe
+- NVIDIA A30 24GB
+- NVIDIA A10 24GB
+- NVIDIA V100 32GB PCIe
+- NVIDIA V100 16GB PCIe
@@ -9,3 +9,4 @@ General-Purpose Graphics Processing Unit Drivers
:numbered:
overview
+ cuda
new file mode 100644
@@ -0,0 +1,716 @@
+/* SPDX-License-Identifier: BSD-3-Clause
+ * Copyright (c) 2021 NVIDIA Corporation & Affiliates
+ */
+
+#include <rte_common.h>
+#include <rte_log.h>
+#include <rte_malloc.h>
+#include <rte_errno.h>
+#include <rte_pci.h>
+#include <rte_bus_pci.h>
+#include <rte_byteorder.h>
+#include <rte_dev.h>
+
+#include <gpudev_driver.h>
+#include <cuda.h>
+
+/* NVIDIA GPU vendor */
+#define NVIDIA_GPU_VENDOR_ID (0x10de)
+
+/* NVIDIA GPU device IDs */
+#define NVIDIA_GPU_A100_40GB_DEVICE_ID (0x20f1)
+#define NVIDIA_GPU_A100_80GB_DEVICE_ID (0x20b5)
+
+#define NVIDIA_GPU_A30_24GB_DEVICE_ID (0x20b7)
+#define NVIDIA_GPU_A10_24GB_DEVICE_ID (0x2236)
+
+#define NVIDIA_GPU_V100_32GB_DEVICE_ID (0x1db6)
+#define NVIDIA_GPU_V100_16GB_DEVICE_ID (0x1db4)
+
+#define CUDA_MAX_ALLOCATION_NUM 512
+
+#define GPU_PAGE_SHIFT 16
+#define GPU_PAGE_SIZE (1UL << GPU_PAGE_SHIFT)
+
+RTE_LOG_REGISTER_DEFAULT(gpu_logtype, NOTICE);
+
+/** Helper macro for logging */
+#define rte_gpu_log(level, fmt, ...) \
+ rte_log(RTE_LOG_ ## level, gpu_logtype, fmt "\n", ##__VA_ARGS__)
+
+#define rte_gpu_log_debug(fmt, ...) \
+ rte_gpu_log(DEBUG, RTE_STR(__LINE__) ":%s() " fmt, __func__, \
+ ##__VA_ARGS__)
+
+/* NVIDIA GPU address map */
+static struct rte_pci_id pci_id_cuda_map[] = {
+ {
+ RTE_PCI_DEVICE(NVIDIA_GPU_VENDOR_ID,
+ NVIDIA_GPU_A100_40GB_DEVICE_ID)
+ },
+ {
+ RTE_PCI_DEVICE(NVIDIA_GPU_VENDOR_ID,
+ NVIDIA_GPU_V100_32GB_DEVICE_ID)
+ },
+ /* {.device_id = 0}, ?? */
+};
+
+/* Device private info */
+struct cuda_info {
+ char gpu_name[RTE_DEV_NAME_MAX_LEN];
+ CUdevice cu_dev;
+};
+
+/* Type of memory allocated by CUDA driver */
+enum mem_type {
+ GPU_MEM = 0,
+ CPU_REGISTERED,
+ GPU_REGISTERED /* Not used yet */
+};
+
+/* key associated to a memory address */
+typedef uintptr_t ptr_key;
+
+/* Single entry of the memory list */
+struct mem_entry {
+ CUdeviceptr ptr_d;
+ void *ptr_h;
+ size_t size;
+ struct rte_gpu *dev;
+ CUcontext ctx;
+ ptr_key pkey;
+ enum mem_type mtype;
+ struct mem_entry *prev;
+ struct mem_entry *next;
+};
+
+struct mem_entry *mem_alloc_list_head = NULL;
+struct mem_entry *mem_alloc_list_tail = NULL;
+uint32_t mem_alloc_list_last_elem = 0;
+
+/* Generate a key from a memory pointer */
+static ptr_key
+get_hash_from_ptr(void *ptr)
+{
+ return (uintptr_t) ptr;
+}
+
+static uint32_t
+mem_list_count_item(void)
+{
+ return mem_alloc_list_last_elem;
+}
+
+/* Initiate list of memory allocations if not done yet */
+static struct mem_entry *
+mem_list_add_item(void)
+{
+ /* Initiate list of memory allocations if not done yet */
+ if (mem_alloc_list_head == NULL) {
+ mem_alloc_list_head = rte_zmalloc(NULL, sizeof(struct mem_entry), RTE_CACHE_LINE_SIZE);
+ if (mem_alloc_list_head == NULL) {
+ rte_gpu_log(ERR, "Failed to allocate memory for memory list.\n");
+ return NULL;
+ }
+
+ mem_alloc_list_head->next = NULL;
+ mem_alloc_list_head->prev = NULL;
+ mem_alloc_list_tail = mem_alloc_list_head;
+ } else {
+ struct mem_entry *mem_alloc_list_cur = rte_zmalloc(NULL, sizeof(struct mem_entry), RTE_CACHE_LINE_SIZE);
+
+ if (mem_alloc_list_cur == NULL) {
+ rte_gpu_log(ERR, "Failed to allocate memory for memory list.\n");
+ return NULL;
+ }
+
+ mem_alloc_list_tail->next = mem_alloc_list_cur;
+ mem_alloc_list_cur->prev = mem_alloc_list_tail;
+ mem_alloc_list_tail = mem_alloc_list_tail->next;
+ mem_alloc_list_tail->next = NULL;
+ }
+
+ mem_alloc_list_last_elem++;
+
+ return mem_alloc_list_tail;
+}
+
+static struct mem_entry *
+mem_list_find_item(ptr_key pk)
+{
+ struct mem_entry *mem_alloc_list_cur = NULL;
+
+ if (mem_alloc_list_head == NULL) {
+ rte_gpu_log(ERR, "Memory list doesn't exist\n");
+ return NULL;
+ }
+
+ if (mem_list_count_item() == 0) {
+ rte_gpu_log(ERR, "No items in memory list\n");
+ return NULL;
+ }
+
+ mem_alloc_list_cur = mem_alloc_list_head;
+
+ while (mem_alloc_list_cur != NULL) {
+ if (mem_alloc_list_cur->pkey == pk)
+ return mem_alloc_list_cur;
+ mem_alloc_list_cur = mem_alloc_list_cur->next;
+ }
+
+ return mem_alloc_list_cur;
+}
+
+static int
+mem_list_del_item(ptr_key pk)
+{
+ struct mem_entry *mem_alloc_list_cur = NULL;
+
+ mem_alloc_list_cur = mem_list_find_item(pk);
+ if (mem_alloc_list_cur == NULL)
+ return -EINVAL;
+
+ /* if key is in head */
+ if (mem_alloc_list_cur->prev == NULL)
+ mem_alloc_list_head = mem_alloc_list_cur->next;
+ else {
+ mem_alloc_list_cur->prev->next = mem_alloc_list_cur->next;
+ if (mem_alloc_list_cur->next != NULL)
+ mem_alloc_list_cur->next->prev = mem_alloc_list_cur->prev;
+ }
+
+ rte_free(mem_alloc_list_cur);
+
+ mem_alloc_list_last_elem--;
+
+ return 0;
+}
+
+static int
+cuda_dev_info_get(struct rte_gpu *dev, struct rte_gpu_info *info)
+{
+ int ret = 0;
+ CUresult res;
+ struct rte_gpu_info parent_info;
+ CUexecAffinityParam affinityPrm;
+ const char *err_string;
+ struct cuda_info *private;
+ CUcontext current_ctx;
+ CUcontext input_ctx;
+
+ if (dev == NULL)
+ return -EINVAL;
+
+ /* Child initialization time probably called by rte_gpu_add_child() */
+ if (dev->mpshared->info.parent != RTE_GPU_ID_NONE && dev->mpshared->dev_private == NULL) {
+ /* Store current ctx */
+ res = cuCtxGetCurrent(¤t_ctx);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxGetCurrent failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ /* Set child ctx as current ctx */
+ input_ctx = (CUcontext)dev->mpshared->info.context;
+ res = cuCtxSetCurrent(input_ctx);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxSetCurrent input failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ /*
+ * Ctx capacity info
+ */
+
+ /* MPS compatible */
+ res = cuCtxGetExecAffinity(&affinityPrm, CU_EXEC_AFFINITY_TYPE_SM_COUNT);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxGetExecAffinity failed with %s.\n", err_string);
+ }
+ dev->mpshared->info.processor_count = (uint32_t)affinityPrm.param.smCount.val;
+
+ ret = rte_gpu_info_get(dev->mpshared->info.parent, &parent_info);
+ if (ret)
+ return -ENODEV;
+ dev->mpshared->info.total_memory = parent_info.total_memory;
+
+ /*
+ * GPU Device private info
+ */
+ dev->mpshared->dev_private = rte_zmalloc(NULL, sizeof(struct cuda_info), RTE_CACHE_LINE_SIZE);
+ if (dev->mpshared->dev_private == NULL) {
+ rte_gpu_log(ERR, "Failed to allocate memory for GPU process private.\n");
+
+ return -1;
+ }
+
+ private = (struct cuda_info *)dev->mpshared->dev_private;
+
+ res = cuCtxGetDevice(&(private->cu_dev));
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxGetDevice failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ res = cuDeviceGetName(private->gpu_name, RTE_DEV_NAME_MAX_LEN, private->cu_dev);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuDeviceGetName failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ /* Restore original ctx as current ctx */
+ res = cuCtxSetCurrent(current_ctx);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxSetCurrent current failed with %s.\n", err_string);
+
+ return -1;
+ }
+ }
+
+ *info = dev->mpshared->info;
+
+ return 0;
+}
+
+/*
+ * GPU Memory
+ */
+
+static int
+cuda_mem_alloc(struct rte_gpu *dev, size_t size, void **ptr)
+{
+ CUresult res;
+ const char *err_string;
+ CUcontext current_ctx;
+ CUcontext input_ctx;
+ unsigned int flag = 1;
+
+ if (dev == NULL || size == 0)
+ return -EINVAL;
+
+ /* Store current ctx */
+ res = cuCtxGetCurrent(¤t_ctx);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxGetCurrent failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ /* Set child ctx as current ctx */
+ input_ctx = (CUcontext)dev->mpshared->info.context;
+ res = cuCtxSetCurrent(input_ctx);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxSetCurrent input failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ /* Get next memory list item */
+ mem_alloc_list_tail = mem_list_add_item();
+ if (mem_alloc_list_tail == NULL)
+ return -ENOMEM;
+
+ /* Allocate memory */
+ mem_alloc_list_tail->size = size;
+ res = cuMemAlloc(&(mem_alloc_list_tail->ptr_d), mem_alloc_list_tail->size);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxSetCurrent current failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ /* GPUDirect RDMA attribute required */
+ res = cuPointerSetAttribute(&flag, CU_POINTER_ATTRIBUTE_SYNC_MEMOPS, mem_alloc_list_tail->ptr_d);
+ if (res != CUDA_SUCCESS) {
+ rte_gpu_log(ERR, "Could not set SYNC MEMOP attribute for GPU memory at %llx , err %d\n", mem_alloc_list_tail->ptr_d, res);
+ return -1;
+ }
+
+ mem_alloc_list_tail->pkey = get_hash_from_ptr((void *) mem_alloc_list_tail->ptr_d);
+ mem_alloc_list_tail->ptr_h = NULL;
+ mem_alloc_list_tail->size = size;
+ mem_alloc_list_tail->dev = dev;
+ mem_alloc_list_tail->ctx = (CUcontext)dev->mpshared->info.context;
+ mem_alloc_list_tail->mtype = GPU_MEM;
+
+ /* Restore original ctx as current ctx */
+ res = cuCtxSetCurrent(current_ctx);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxSetCurrent current failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ *ptr = (void *) mem_alloc_list_tail->ptr_d;
+
+ return 0;
+}
+
+static int
+cuda_mem_register(struct rte_gpu *dev, size_t size, void *ptr)
+{
+ CUresult res;
+ const char *err_string;
+ CUcontext current_ctx;
+ CUcontext input_ctx;
+ unsigned int flag = 1;
+ int use_ptr_h = 0;
+
+ if (dev == NULL || size == 0 || ptr == NULL)
+ return -EINVAL;
+
+ /* Store current ctx */
+ res = cuCtxGetCurrent(¤t_ctx);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxGetCurrent failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ /* Set child ctx as current ctx */
+ input_ctx = (CUcontext)dev->mpshared->info.context;
+ res = cuCtxSetCurrent(input_ctx);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxSetCurrent input failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ /* Get next memory list item */
+ mem_alloc_list_tail = mem_list_add_item();
+ if (mem_alloc_list_tail == NULL)
+ return -ENOMEM;
+
+ /* Allocate memory */
+ mem_alloc_list_tail->size = size;
+ mem_alloc_list_tail->ptr_h = ptr;
+
+ res = cuMemHostRegister(mem_alloc_list_tail->ptr_h, mem_alloc_list_tail->size, CU_MEMHOSTREGISTER_PORTABLE | CU_MEMHOSTREGISTER_DEVICEMAP);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuMemHostRegister failed with %s ptr %p size %zd.\n",
+ err_string, mem_alloc_list_tail->ptr_h, mem_alloc_list_tail->size
+ );
+
+ return -1;
+ }
+
+ res = cuDeviceGetAttribute(&(use_ptr_h),
+ CU_DEVICE_ATTRIBUTE_CAN_USE_HOST_POINTER_FOR_REGISTERED_MEM,
+ ((struct cuda_info *)(dev->mpshared->dev_private))->cu_dev
+ );
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuDeviceGetAttribute failed with %s.\n",
+ err_string
+ );
+
+ return -1;
+ }
+
+ if (use_ptr_h == 0) {
+ res = cuMemHostGetDevicePointer(&(mem_alloc_list_tail->ptr_d), mem_alloc_list_tail->ptr_h, 0);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuMemHostGetDevicePointer failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ if ((uintptr_t) mem_alloc_list_tail->ptr_d != (uintptr_t) mem_alloc_list_tail->ptr_h) {
+ rte_gpu_log(ERR, "Host input pointer is different wrt GPU registered pointer\n");
+ return -1;
+ }
+ } else {
+ mem_alloc_list_tail->ptr_d = (CUdeviceptr) mem_alloc_list_tail->ptr_h;
+ }
+
+ /* GPUDirect RDMA attribute required */
+ res = cuPointerSetAttribute(&flag, CU_POINTER_ATTRIBUTE_SYNC_MEMOPS, mem_alloc_list_tail->ptr_d);
+ if (res != CUDA_SUCCESS) {
+ rte_gpu_log(ERR, "Could not set SYNC MEMOP attribute for GPU memory at %llx , err %d\n", mem_alloc_list_tail->ptr_d, res);
+ return -1;
+ }
+
+ mem_alloc_list_tail->pkey = get_hash_from_ptr((void *) mem_alloc_list_tail->ptr_h);
+ mem_alloc_list_tail->size = size;
+ mem_alloc_list_tail->dev = dev;
+ mem_alloc_list_tail->ctx = (CUcontext)dev->mpshared->info.context;
+ mem_alloc_list_tail->mtype = CPU_REGISTERED;
+
+ /* Restore original ctx as current ctx */
+ res = cuCtxSetCurrent(current_ctx);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuCtxSetCurrent current failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ return 0;
+}
+
+static int
+cuda_mem_free(struct rte_gpu *dev, void *ptr)
+{
+ CUresult res;
+ struct mem_entry *mem_item;
+ const char *err_string;
+ ptr_key hk;
+
+ if (dev == NULL || ptr == NULL)
+ return -EINVAL;
+
+ hk = get_hash_from_ptr((void *) ptr);
+
+ mem_item = mem_list_find_item(hk);
+ if (mem_item == NULL) {
+ rte_gpu_log(ERR, "Memory address 0x%p not found in driver memory\n", ptr);
+ return -1;
+ }
+
+ if (mem_item->mtype == GPU_MEM) {
+ res = cuMemFree(mem_item->ptr_d);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuMemFree current failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ return mem_list_del_item(hk);
+
+ } else {
+ rte_gpu_log(ERR, "Memory type %d not supported\n", mem_item->mtype);
+ return -1;
+ }
+
+ return 0;
+}
+
+static int
+cuda_mem_unregister(struct rte_gpu *dev, void *ptr)
+{
+ CUresult res;
+ struct mem_entry *mem_item;
+ const char *err_string;
+ ptr_key hk;
+
+ if (dev == NULL || ptr == NULL)
+ return -EINVAL;
+
+ hk = get_hash_from_ptr((void *) ptr);
+
+ mem_item = mem_list_find_item(hk);
+ if (mem_item == NULL) {
+ rte_gpu_log(ERR, "Memory address 0x%p not nd in driver memory\n", ptr);
+ return -1;
+ }
+
+ if (mem_item->mtype == CPU_REGISTERED) {
+ res = cuMemHostUnregister(ptr);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuMemHostUnregister current failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ return mem_list_del_item(hk);
+ } else {
+ rte_gpu_log(ERR, "Memory type %d not supported\n", mem_item->mtype);
+ return -1;
+ }
+
+ return 0;
+}
+
+static int
+cuda_dev_close(struct rte_gpu *dev)
+{
+ if (dev == NULL)
+ return -EINVAL;
+
+ rte_free(dev->mpshared->dev_private);
+
+ return 0;
+}
+
+static int
+cuda_gpu_probe(__rte_unused struct rte_pci_driver *pci_drv, struct rte_pci_device *pci_dev)
+{
+ struct rte_gpu *dev = NULL;
+ CUresult res;
+ CUdevice cu_dev_id;
+ CUcontext pctx;
+ char dev_name[RTE_DEV_NAME_MAX_LEN];
+ const char *err_string;
+ int processor_count = 0;
+ struct cuda_info *private;
+
+ if (pci_dev == NULL) {
+ rte_gpu_log(ERR, "NULL PCI device");
+ return -EINVAL;
+ }
+
+ rte_pci_device_name(&pci_dev->addr, dev_name, sizeof(dev_name));
+
+ /* Allocate memory to be used privately by drivers */
+ dev = rte_gpu_allocate(pci_dev->device.name);
+ if (dev == NULL)
+ return -ENODEV;
+
+ /* Fill HW specific part of device structure */
+ dev->device = &pci_dev->device;
+ dev->mpshared->info.numa_node = pci_dev->device.numa_node;
+
+ /*
+ * GPU Device init
+ */
+
+ /*
+ * Required to initialize the CUDA Driver.
+ * Multiple calls of cuInit() will return immediately
+ * without making any relevant change
+ */
+ cuInit(0);
+
+ /* Get NVIDIA GPU Device descriptor */
+ res = cuDeviceGetByPCIBusId(&cu_dev_id, dev->device->name);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuDeviceGetByPCIBusId name %s failed with %d: %s.\n",
+ dev->device->name, res, err_string
+ );
+
+ return -1;
+ }
+
+ res = cuDevicePrimaryCtxRetain(&pctx, cu_dev_id);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuDevicePrimaryCtxRetain name %s failed with %d: %s.\n",
+ dev->device->name, res, err_string
+ );
+
+ return -1;
+ }
+
+ dev->mpshared->info.context = (uint64_t) pctx;
+
+ /*
+ * GPU Device generic info
+ */
+
+ /* Processor count */
+ res = cuDeviceGetAttribute(&(processor_count), CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, cu_dev_id);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuDeviceGetAttribute failed with %s.\n",
+ err_string
+ );
+
+ return -1;
+ }
+ dev->mpshared->info.processor_count = (uint32_t)processor_count;
+
+ /* Total memory */
+ res = cuDeviceTotalMem(&dev->mpshared->info.total_memory, cu_dev_id);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuDeviceTotalMem failed with %s.\n",
+ err_string
+ );
+
+ return -1;
+ }
+
+ /*
+ * GPU Device private info
+ */
+ dev->mpshared->dev_private = rte_zmalloc(NULL, sizeof(struct cuda_info), RTE_CACHE_LINE_SIZE);
+ if (dev->mpshared->dev_private == NULL) {
+ rte_gpu_log(ERR, "Failed to allocate memory for GPU process private.\n");
+
+ return -1;
+ }
+
+ private = (struct cuda_info *)dev->mpshared->dev_private;
+ private->cu_dev = cu_dev_id;
+ res = cuDeviceGetName(private->gpu_name, RTE_DEV_NAME_MAX_LEN, cu_dev_id);
+ if (res != CUDA_SUCCESS) {
+ cuGetErrorString(res, &(err_string));
+ rte_gpu_log(ERR, "cuDeviceGetName failed with %s.\n", err_string);
+
+ return -1;
+ }
+
+ dev->ops.mem_alloc = cuda_mem_alloc;
+ dev->ops.mem_free = cuda_mem_free;
+ dev->ops.mem_register = cuda_mem_register;
+ dev->ops.mem_unregister = cuda_mem_unregister;
+ dev->ops.dev_info_get = cuda_dev_info_get;
+ dev->ops.dev_close = cuda_dev_close;
+
+ rte_gpu_complete_new(dev);
+
+ rte_gpu_log_debug("dev id = %u name = %s\n", dev->mpshared->info.dev_id, private->gpu_name);
+
+ return 0;
+}
+
+static int
+cuda_gpu_remove(struct rte_pci_device *pci_dev)
+{
+ struct rte_gpu *dev;
+ int ret;
+ uint8_t gpu_id;
+
+ if (pci_dev == NULL)
+ return -EINVAL;
+
+ dev = rte_gpu_get_by_name(pci_dev->device.name);
+ if (dev == NULL) {
+ rte_gpu_log(ERR,
+ "Couldn't find HW dev \"%s\" to uninitialise it",
+ pci_dev->device.name);
+ return -ENODEV;
+ }
+ gpu_id = dev->mpshared->info.dev_id;
+
+ /* release dev from library */
+ ret = rte_gpu_release(dev);
+ if (ret)
+ rte_gpu_log(ERR, "Device %i failed to uninit: %i", gpu_id, ret);
+
+ rte_gpu_log_debug("Destroyed dev = %u", gpu_id);
+
+ return 0;
+}
+
+static struct rte_pci_driver rte_cuda_driver = {
+ .id_table = pci_id_cuda_map,
+ .drv_flags = RTE_PCI_DRV_WC_ACTIVATE,
+ .probe = cuda_gpu_probe,
+ .remove = cuda_gpu_remove,
+};
+
+RTE_PMD_REGISTER_PCI(gpu_cuda, rte_cuda_driver);
+RTE_PMD_REGISTER_PCI_TABLE(gpu_cuda, pci_id_cuda_map);
+RTE_PMD_REGISTER_KMOD_DEP(gpu_cuda, "* nvidia & (nv_peer_mem | nvpeer_mem)");
new file mode 100644
@@ -0,0 +1,30 @@
+# SPDX-License-Identifier: BSD-3-Clause
+# Copyright (c) 2021 NVIDIA Corporation & Affiliates
+
+if not is_linux
+ build = false
+ reason = 'only supported on Linux'
+endif
+
+# cuda_dep = dependency('cuda-11.1', required: true, version : '>=11.1', method: 'pkg-config')
+# if not cuda_dep.found()
+# build = false
+# reason = 'missing dependency, "CUDA"'
+# subdir_done()
+# endif
+# ext_deps += cuda_dep
+
+cuda_dep = dependency('cuda', version : '>=11', modules: ['cuda'])
+ext_deps += cuda_dep
+
+# cudart_dep = dependency('cudart-11.1', required: true, version : '>=11.1', method: 'pkg-config')
+# if not cudart_dep.found()
+# build = false
+# reason = 'missing dependency, "CUDA RT"'
+# subdir_done()
+# endif
+# ext_deps += cudart_dep
+
+deps += ['gpudev','pci','bus_pci', 'hash']
+sources = files('cuda.c')
+# headers = files('header.h')
new file mode 100644
@@ -0,0 +1,3 @@
+DPDK_21 {
+ local: *;
+};
@@ -1,4 +1,4 @@
# SPDX-License-Identifier: BSD-3-Clause
# Copyright (c) 2021 NVIDIA Corporation & Affiliates
-drivers = []
+drivers = [ 'cuda' ]