diff mbox series

[RFC] gpu/cuda: introduce CUDA driver

Message ID 20211005224905.13505-1-eagostini@nvidia.com (mailing list archive)
State Superseded, archived
Delegated to: Thomas Monjalon
Headers show
Series [RFC] gpu/cuda: introduce CUDA driver | expand

Checks

Context Check Description
ci/Intel-compilation warning apply issues
ci/checkpatch warning coding style issues

Commit Message

Elena Agostini Oct. 5, 2021, 10:49 p.m. UTC
From: Elena Agostini <eagostini@nvidia.com>

This is the CUDA implementation of the gpudev library.
Funcitonalities implemented through CUDA Driver API are:

- Device probe and remove
- Manage device memory allocations
- Register/unregister external CPU memory in the device memory area

Signed-off-by: Elena Agostini <eagostini@nvidia.com>
---
 drivers/gpu/cuda/cuda.c      | 751 +++++++++++++++++++++++++++++++++++
 drivers/gpu/cuda/meson.build |  30 ++
 drivers/gpu/cuda/version.map |   3 +
 drivers/gpu/meson.build      |   2 +-
 4 files changed, 785 insertions(+), 1 deletion(-)
 create mode 100644 drivers/gpu/cuda/cuda.c
 create mode 100644 drivers/gpu/cuda/meson.build
 create mode 100644 drivers/gpu/cuda/version.map

Comments

Stephen Hemminger Nov. 8, 2021, 7:02 p.m. UTC | #1
On Tue, 5 Oct 2021 22:49:05 +0000
<eagostini@nvidia.com> wrote:

> From: Elena Agostini <eagostini@nvidia.com>
> 
> This is the CUDA implementation of the gpudev library.
> Funcitonalities implemented through CUDA Driver API are:
> 
> - Device probe and remove
> - Manage device memory allocations
> - Register/unregister external CPU memory in the device memory area
> 
> Signed-off-by: Elena Agostini <eagostini@nvidia.com>
> ---

What is the license of the CUDA Driver?
Elena Agostini Nov. 8, 2021, 9:20 p.m. UTC | #2
> From: Stephen Hemminger <stephen@networkplumber.org>
> Date: Monday, 8 November 2021 at 20:02
> To: Elena Agostini <eagostini@nvidia.com>
> Cc: dev@dpdk.org <dev@dpdk.org>
> Subject: Re: [dpdk-dev] [RFC PATCH] gpu/cuda: introduce CUDA driver
> External email: Use caution opening links or attachments
>
>
> On Tue, 5 Oct 2021 22:49:05 +0000
> <eagostini@nvidia.com> wrote:
>
> > From: Elena Agostini <eagostini@nvidia.com>
> >
> > This is the CUDA implementation of the gpudev library.
> > Funcitonalities implemented through CUDA Driver API are:
> >
> > - Device probe and remove
> > - Manage device memory allocations
> > - Register/unregister external CPU memory in the device memory area
> >
> > Signed-off-by: Elena Agostini <eagostini@nvidia.com>
> > ---
>
> What is the license of the CUDA Driver?

As you can see in the code:
/* SPDX-License-Identifier: BSD-3-Clause
* Copyright (c) 2021 NVIDIA Corporation & Affiliates
*/
Stephen Hemminger Nov. 8, 2021, 10:07 p.m. UTC | #3
On Mon, 8 Nov 2021 21:20:31 +0000
Elena Agostini <eagostini@nvidia.com> wrote:

> > From: Stephen Hemminger <stephen@networkplumber.org>
> > Date: Monday, 8 November 2021 at 20:02
> > To: Elena Agostini <eagostini@nvidia.com>
> > Cc: dev@dpdk.org <dev@dpdk.org>
> > Subject: Re: [dpdk-dev] [RFC PATCH] gpu/cuda: introduce CUDA driver
> > External email: Use caution opening links or attachments
> >
> >
> > On Tue, 5 Oct 2021 22:49:05 +0000
> > <eagostini@nvidia.com> wrote:
> >  
> > > From: Elena Agostini <eagostini@nvidia.com>
> > >
> > > This is the CUDA implementation of the gpudev library.
> > > Funcitonalities implemented through CUDA Driver API are:
> > >
> > > - Device probe and remove
> > > - Manage device memory allocations
> > > - Register/unregister external CPU memory in the device memory area
> > >
> > > Signed-off-by: Elena Agostini <eagostini@nvidia.com>
> > > ---  
> >
> > What is the license of the CUDA Driver?  
> 

I meant the CUDA driver API?
The DPDK policy is that driver can not be a wrapper around a
close source API.
Stephen Hemminger Nov. 8, 2021, 11:15 p.m. UTC | #4
On Mon, 8 Nov 2021 14:07:47 -0800
Stephen Hemminger <stephen@networkplumber.org> wrote:

> On Mon, 8 Nov 2021 21:20:31 +0000
> Elena Agostini <eagostini@nvidia.com> wrote:
> 
> > > From: Stephen Hemminger <stephen@networkplumber.org>
> > > Date: Monday, 8 November 2021 at 20:02
> > > To: Elena Agostini <eagostini@nvidia.com>
> > > Cc: dev@dpdk.org <dev@dpdk.org>
> > > Subject: Re: [dpdk-dev] [RFC PATCH] gpu/cuda: introduce CUDA driver
> > > External email: Use caution opening links or attachments
> > >
> > >
> > > On Tue, 5 Oct 2021 22:49:05 +0000
> > > <eagostini@nvidia.com> wrote:
> > >    
> > > > From: Elena Agostini <eagostini@nvidia.com>
> > > >
> > > > This is the CUDA implementation of the gpudev library.
> > > > Funcitonalities implemented through CUDA Driver API are:
> > > >
> > > > - Device probe and remove
> > > > - Manage device memory allocations
> > > > - Register/unregister external CPU memory in the device memory area
> > > >
> > > > Signed-off-by: Elena Agostini <eagostini@nvidia.com>
> > > > ---    
> > >
> > > What is the license of the CUDA Driver?    
> >   
> 
> I meant the CUDA driver API?
> The DPDK policy is that driver can not be a wrapper around a
> close source API.

If it is this license agreement from Nvidia 
https://docs.nvidia.com/cuda/eula/index.html

Then it is clearly not open source and I would have to recommend
against allowing this driver in DPDK. 

Corollary: without a open-source GPU driver, I would also recommend
against including the GPU driver subsystem in DPDK.

Note: these views are my own as part of the open-source community
and do not represent those of my employer.
diff mbox series

Patch

diff --git a/drivers/gpu/cuda/cuda.c b/drivers/gpu/cuda/cuda.c
new file mode 100644
index 0000000000..202f0a0c0c
--- /dev/null
+++ b/drivers/gpu/cuda/cuda.c
@@ -0,0 +1,751 @@ 
+/* 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_V100_32GB_DEVICE_ID (0x1db6)
+
+#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(&current_ctx);
+		if(CUDA_SUCCESS != res)
+		{
+			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(CUDA_SUCCESS != res)
+		{
+			cuGetErrorString(res, &(err_string));
+			rte_gpu_log(ERR, "cuda_dev_info_get 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(CUDA_SUCCESS != res)
+		{
+			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(CUDA_SUCCESS != res)
+		{
+			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(CUDA_SUCCESS != res)
+		{
+			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(CUDA_SUCCESS != res)
+		{
+			cuGetErrorString(res, &(err_string));
+			rte_gpu_log(ERR, "cuda_dev_info_get 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(&current_ctx);
+	if(CUDA_SUCCESS != res)
+	{
+		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(CUDA_SUCCESS != res)
+	{
+		cuGetErrorString(res, &(err_string));
+		rte_gpu_log(ERR, "cuda_mem_alloc 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 (CUDA_SUCCESS != res) {
+		cuGetErrorString(res, &(err_string));
+		rte_gpu_log(ERR, "cuda_mem_alloc 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 (CUDA_SUCCESS != res) {
+		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(CUDA_SUCCESS != res)
+	{
+		cuGetErrorString(res, &(err_string));
+		rte_gpu_log(ERR, "cuda_mem_alloc 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(&current_ctx);
+	if(CUDA_SUCCESS != res)
+	{
+		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(CUDA_SUCCESS != res)
+	{
+		cuGetErrorString(res, &(err_string));
+		rte_gpu_log(ERR, "cuda_mem_register 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 (CUDA_SUCCESS != res) {
+		cuGetErrorString(res, &(err_string));
+		rte_gpu_log(ERR, "cuda_mem_register 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(CUDA_SUCCESS != res)
+	{
+		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 (CUDA_SUCCESS != res) {
+			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 (CUDA_SUCCESS != res) {
+		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(CUDA_SUCCESS != res)
+	{
+		cuGetErrorString(res, &(err_string));
+		rte_gpu_log(ERR, "cuda_mem_register 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(CUDA_SUCCESS != res)
+		{
+			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(CUDA_SUCCESS != res)
+		{
+			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(CUDA_SUCCESS != res)
+	{
+		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(CUDA_SUCCESS != res)
+	{
+		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(CUDA_SUCCESS != res)
+	{
+		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(CUDA_SUCCESS != res)
+	{
+		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(CUDA_SUCCESS != res)
+	{
+		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)");
+
diff --git a/drivers/gpu/cuda/meson.build b/drivers/gpu/cuda/meson.build
new file mode 100644
index 0000000000..53e40e6832
--- /dev/null
+++ b/drivers/gpu/cuda/meson.build
@@ -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')
diff --git a/drivers/gpu/cuda/version.map b/drivers/gpu/cuda/version.map
new file mode 100644
index 0000000000..4a76d1d52d
--- /dev/null
+++ b/drivers/gpu/cuda/version.map
@@ -0,0 +1,3 @@ 
+DPDK_21 {
+	local: *;
+};
diff --git a/drivers/gpu/meson.build b/drivers/gpu/meson.build
index e51ad3381b..601bedcd61 100644
--- a/drivers/gpu/meson.build
+++ b/drivers/gpu/meson.build
@@ -1,4 +1,4 @@ 
 # SPDX-License-Identifier: BSD-3-Clause
 # Copyright (c) 2021 NVIDIA Corporation & Affiliates
 
-drivers = []
+drivers = [ 'cuda' ]