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CHANGELOG.md

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Changelog

CUDA 12.4

  • Added graphConditionalNodes Sample

CUDA 12.3

  • Added cuDLA samples
  • Fixed jitLto regression

CUDA 12.2

  • libNVVM samples received updates
  • Fixed jitLto Case issues
  • Enabled HOST_COMPILER flag to the makefiles for GCC which is untested but may still work.

CUDA 12.1

  • Added new sample for Large Kernels

CUDA 12.0

  • Added new flags for JIT compiling
  • Removed deprecated APIs in Hopper Architecture

CUDA 11.6

  • Added new folder structure for samples
  • Added support of Visual Studio 2022 to all samples supported on Windows.
  • All CUDA samples are now only available on GitHub. They are no longer available via CUDA toolkit.

CUDA 11.5

  • 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.

CUDA 11.4 update 1

  • Added support for VS Code on linux platform.

CUDA 11.4

  • Added cdpQuadtree. Demonstrates Quad Trees implementation using CUDA Dynamic Parallelism.
  • Updated simpleVulkan, simpleVulkanMMAP and vulkanImageCUDA. Demonstrates use of SPIR-V shaders.

CUDA 11.3

  • Added streamOrderedAllocationIPC. Demonstrates Inter Process Communication using one process per GPU for computation.
  • Added simpleCUBLAS_LU. Demonstrates batched matrix LU decomposition using cuBLAS API cublas<t>getrfBatched()
  • Updated simpleVulkan. Demonstrates use of timeline semaphore.
  • Updated multiple samples to use pinned memory using cudaMallocHost().

CUDA 11.2

  • 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 and cuda::barrier interfaces.
  • Updated all the samples to build with parallel build option --threads of nvcc cuda compiler.
  • Added cudaNvSciNvMedia. Demonstrates CUDA-NvMedia interop via NvSciBuf/NvSciSync APIs.
  • Added simpleGL. Demonstrates interoperability between CUDA and OpenGL.

CUDA 11.1

  • 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.

CUDA 11.0

  • 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.

CUDA 10.2

  • 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.

CUDA 10.1 Update 2

  • 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.

CUDA 10.1 Update 1

  • 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.

CUDA 10.1

  • 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.

CUDA 10.0

  • 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.

CUDA 9.2

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.