- Added
cuDLAHybridMode
. Demonstrate usage of cuDLA in hybrid mode. - Added
cuDLAStandaloneMode
. Demonstrate usage of cuDLA in standalone mode. - Added
cuDLAErrorReporting
. Demonstrate DLA error detection via CUDA. - Added
graphMemoryNodes
. Demonstrates memory allocations and frees within CUDA graphs using Graph APIs and Stream Capture APIs. - Added
graphMemoryFootprint
. Demonstrates how graph memory nodes re-use virtual addresses and physical memory. - All samples from CUDA toolkit are now available on GitHub.
- Added support for VS Code on linux platform.
- Added
cdpQuadtree
. Demonstrates Quad Trees implementation using CUDA Dynamic Parallelism. - Updated
simpleVulkan
,simpleVulkanMMAP
andvulkanImageCUDA
. Demonstrates use of SPIR-V shaders.
- Added
streamOrderedAllocationIPC
. Demonstrates Inter Process Communication using one process per GPU for computation. - Added
simpleCUBLAS_LU
. Demonstrates batched matrix LU decomposition using cuBLAS APIcublas<t>getrfBatched()
- Updated
simpleVulkan
. Demonstrates use of timeline semaphore. - Updated multiple samples to use pinned memory using
cudaMallocHost()
.
- Added
streamOrderedAllocation
. Demonstrates stream ordered memory allocation on a GPU using cudaMallocAsync and cudaMemPool family of APIs. - Added
streamOrderedAllocationP2P
. Demonstrates peer-to-peer access of stream ordered memory allocated using cudaMallocAsync and cudaMemPool family of APIs. - Dropped Visual Studio 2015 support from all the windows supported samples.
- FreeImage is no longer distributed with the CUDA Samples. On Windows, see the Dependencies section for more details on how to set up FreeImage. On Linux, it is recommended to install FreeImage with your distribution's package manager.
- All the samples using CUDA Pipeline & Arrive-wait barriers are been updated to use new
cuda::pipeline
andcuda::barrier
interfaces. - Updated all the samples to build with parallel build option
--threads
ofnvcc
cuda compiler. - Added
cudaNvSciNvMedia
. Demonstrates CUDA-NvMedia interop via NvSciBuf/NvSciSync APIs. - Added
simpleGL
. Demonstrates interoperability between CUDA and OpenGL.
- Added
watershedSegmentationNPP
. Demonstrates how to use the NPP watershed segmentation function. - Added
batchedLabelMarkersAndLabelCompressionNPP
. Demonstrates how to use the NPP label markers generation and label compression functions based on a Union Find (UF) algorithm including both single image and batched image versions. - Dropped Visual Studio 2012, 2013 support from all the windows supported samples.
- Added kernel performing warp aggregated atomic max in multi buckets using cg::labeled_partition & cg::reduce in
warpAggregatedAtomicsCG
. - Added extended CG shuffle mechanics to
shfl_scan
sample. - Added
cudaOpenMP
. Demonstrates how to use OpenMP API to write an application for multiple GPUs. - Added
simpleZeroCopy
. Demonstrates how to use zero copy, kernels can read and write directly to pinned system memory.
- Added
dmmaTensorCoreGemm
. Demonstrates double precision GEMM computation using the Double precision Warp Matrix Multiply and Accumulate (WMMA) API introduced with CUDA 11 in Ampere chip family tensor cores. - Added
bf16TensorCoreGemm
. Demonstrates __nv_bfloat16 (e8m7) GEMM computation using the __nv_bfloat16 WMMA API introduced with CUDA 11 in Ampere chip family tensor cores. - Added
tf32TensorCoreGemm
. Demonstrates tf32 (e8m10) GEMM computation using the tf32 WMMA API introduced with CUDA 11 in Ampere chip family tensor cores. - Added
globalToShmemAsyncCopy
. Demonstrates async copy of data from global to shared memory when on compute capability 8.0 or higher. Also demonstrates arrive-wait barrier for synchronization. - Added
simpleAWBarrier
. Demonstrates arrive wait barriers. - Added
simpleAttributes
. Demonstrates the stream attributes that affect L2 locality. - Added warp aggregated atomic multi bucket increments kernel using labeled_partition cooperative groups in
warpAggregatedAtomicsCG
which can be used on compute capability 7.0 and above GPU architectures. - Added
binaryPartitionCG
. Demonstrates binary partition cooperative groups and reduction within the thread block. - Added two new reduction kernels in
reduction
one which demonstrates reduce_add_sync intrinstic supported on compute capability 8.0 and another which uses cooperative_groups::reduce function which does thread_block_tile level reduction introduced from CUDA 11.0. - Added
cudaCompressibleMemory
. Demonstrates compressible memory allocation using cuMemMap API. - Added
simpleVulkanMMAP
. Demonstrates Vulkan CUDA Interop via cuMemMap APIs. - Added
concurrentKernels
. Demonstrates the use of CUDA streams for concurrent execution of several kernels on a GPU. - Dropped Mac OSX support from all samples.
- Added
simpleD3D11
. Demonstrates CUDA-D3D11 External Resource Interoperability APIs for updating D3D11 buffers from CUDA and synchronization between D3D11 and CUDA with Keyed Mutexes. - Added
simpleDrvRuntime
. Demonstrates CUDA Driver and Runtime APIs working together to load fatbinary of a CUDA kernel. - Added
vectorAddMMAP
. Demonstrates how cuMemMap API allows the user to specify the physical properties of their memory while retaining the contiguous nature of their access. - Added
memMapIPCDrv
. Demonstrates Inter Process Communication using cuMemMap APIs. - Added
cudaNvSci
. Demonstrates CUDA-NvSciBuf/NvSciSync Interop. - Added
jacobiCudaGraphs
. Demonstrates Instantiated CUDA Graph Update with Jacobi Iterative Method using different approaches. - Added
cuSolverSp_LinearSolver
. Demonstrates cuSolverSP's LU, QR and Cholesky factorization. - Added
MersenneTwisterGP11213
. Demonstrates the Mersenne Twister random number generator GP11213 in cuRAND.
- Added
vulkanImageCUDA
. Demonstrates how to perform Vulkan image - CUDA Interop. - Added
nvJPEG_encoder
. Demonstrates encoding of jpeg images using NVJPEG Library. - Added Windows OS support to
nvJPEG
sample. - Added
boxFilterNPP
. Demonstrates how to use NPP FilterBox function to perform a box filter. - Added
cannyEdgeDetectorNPP
. Demonstrates the nppiFilterCannyBorder_8u_C1R Canny Edge Detection image filter function.
- Added
NV12toBGRandResize
. Demonstrates how to convert and resize NV12 frames to BGR planars frames using CUDA in batch. - Added
EGLStream_CUDA_Interop
. Demonstrates data exchange between CUDA and EGL Streams. - Added
cuSolverDn_LinearSolver
. Demonstrates cuSolverDN's LU, QR and Cholesky factorization. - Added support of Visual Studio 2019 to all samples supported on Windows.
- Added
immaTensorCoreGemm
. Demonstrates integer GEMM computation using the Warp Matrix Multiply and Accumulate (WMMA) API for integers employing the Tensor Cores. - Added
simpleIPC
. Demonstrates Inter Process Communication with one process per GPU for computation. - Added
nvJPEG
. Demonstrates single and batched decoding of jpeg images using NVJPEG Library. - Added
bandwidthTest
. It measures the memcopy bandwidth of the GPU and memcpy bandwidth across PCI-e. - Added
reduction
. Demonstrates several important optimization strategies for Data-Parallel Algorithms like reduction. - Update all the samples to support CUDA 10.1.
- Added
simpleCudaGraphs
. Demonstrates CUDA Graphs creation, instantiation and launch using Graphs APIs and Stream Capture APIs. - Added
conjugateGradientCudaGraphs
. Demonstrates conjugate gradient solver on GPU using CUBLAS and CUSPARSE library calls captured and called using CUDA Graph APIs. - Added
simpleVulkan
. Demonstrates Vulkan - CUDA Interop. - Added
simpleD3D12
. Demonstrates DX12 - CUDA Interop. - Added
UnifiedMemoryPerf
. Demonstrates performance comparision of various memory types involved in system. - Added
p2pBandwidthLatencyTest
. Demonstrates Peer-To-Peer (P2P) data transfers between pairs of GPUs and computes latency and bandwidth. - Added
systemWideAtomics
. Demonstrates system wide atomic instructions. - Added
simpleCUBLASXT
. Demonstrates CUBLAS-XT library which performs GEMM operations over multiple GPUs. - Added Windows OS support to
conjugateGradientMultiDeviceCG
sample. - Removed support of Visual Studio 2010 from all samples.
This is the first release of CUDA Samples on GitHub:
- Added
vectorAdd_nvrtc
. Demonstrates runtime compilation library using NVRTC of a simple vectorAdd kernel. - Added
warpAggregatedAtomicsCG
. Demonstrates warp aggregated atomics using Cooperative Groups. - Added
deviceQuery
. Enumerates the properties of the CUDA devices present in the system. - Added
matrixMul
. Demonstrates a matrix multiplication using shared memory through tiled approach. - Added
matrixMulDrv
. Demonstrates a matrix multiplication using shared memory through tiled approach, uses CUDA Driver API. - Added
cudaTensorCoreGemm
. Demonstrates a GEMM computation using the Warp Matrix Multiply and Accumulate (WMMA) API introduced in CUDA 9, as well as the new Tensor Cores introduced in the Volta chip family. - Added
simpleVoteIntrinsics
which uses *_sync equivalent of the vote intrinsics _any, _all added since CUDA 9.0. - Added
shfl_scan
which uses *_sync equivalent of the shfl intrinsics added since CUDA 9.0. - Added
conjugateGradientMultiBlockCG
. Demonstrates a conjugate gradient solver on GPU using Multi Block Cooperative Groups. - Added
conjugateGradientMultiDeviceCG
. Demonstrates a conjugate gradient solver on multiple GPUs using Multi Device Cooperative Groups, also uses unified memory prefetching and usage hints APIs. - Added
simpleCUBLAS
. Demonstrates how perform GEMM operations using CUBLAS library. - Added
simpleCUFFT
. Demonstrates how perform FFT operations using CUFFT library.