mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2024-10-06 05:49:16 +08:00
144 lines
11 KiB
Markdown
144 lines
11 KiB
Markdown
## Changelog
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### CUDA 12.5
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### CUDA 12.4
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* Added graphConditionalNodes Sample
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### CUDA 12.3
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* Added cuDLA samples
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* Fixed jitLto regression
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### CUDA 12.2
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* libNVVM samples received updates
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* Fixed jitLto Case issues
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* Enabled HOST_COMPILER flag to the makefiles for GCC which is untested but may still work.
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### CUDA 12.1
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* Added new sample for Large Kernels
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### CUDA 12.0
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* Added new flags for JIT compiling
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* Removed deprecated APIs in Hopper Architecture
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### CUDA 11.6
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* Added new folder structure for samples
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* Added support of Visual Studio 2022 to all samples supported on [Windows](#windows-1).
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* All CUDA samples are now only available on [GitHub](https://github.com/nvidia/cuda-samples). They are no longer available via CUDA toolkit.
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### CUDA 11.5
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* Added `cuDLAHybridMode`. Demonstrate usage of cuDLA in hybrid mode.
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* Added `cuDLAStandaloneMode`. Demonstrate usage of cuDLA in standalone mode.
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* Added `cuDLAErrorReporting`. Demonstrate DLA error detection via CUDA.
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* Added `graphMemoryNodes`. Demonstrates memory allocations and frees within CUDA graphs using Graph APIs and Stream Capture APIs.
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* Added `graphMemoryFootprint`. Demonstrates how graph memory nodes re-use virtual addresses and physical memory.
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* All samples from CUDA toolkit are now available on [GitHub](https://github.com/nvidia/cuda-samples).
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### CUDA 11.4 update 1
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* Added support for VS Code on linux platform.
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### CUDA 11.4
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* Added `cdpQuadtree`. Demonstrates Quad Trees implementation using CUDA Dynamic Parallelism.
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* Updated `simpleVulkan`, `simpleVulkanMMAP` and `vulkanImageCUDA`. Demonstrates use of SPIR-V shaders.
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### CUDA 11.3
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* Added `streamOrderedAllocationIPC`. Demonstrates Inter Process Communication using one process per GPU for computation.
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* Added `simpleCUBLAS_LU`. Demonstrates batched matrix LU decomposition using cuBLAS API `cublas<t>getrfBatched()`
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* Updated `simpleVulkan`. Demonstrates use of timeline semaphore.
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* Updated multiple samples to use pinned memory using `cudaMallocHost()`.
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### CUDA 11.2
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* Added `streamOrderedAllocation`. Demonstrates stream ordered memory allocation on a GPU using cudaMallocAsync and cudaMemPool family of APIs.
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* Added `streamOrderedAllocationP2P`. Demonstrates peer-to-peer access of stream ordered memory allocated using cudaMallocAsync and cudaMemPool family of APIs.
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* Dropped Visual Studio 2015 support from all the windows supported samples.
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* FreeImage is no longer distributed with the CUDA Samples. On Windows, see the [Dependencies](./README.md#freeimage) section for more details on how to set up FreeImage. On Linux, it is recommended to install FreeImage with your distribution's package manager.
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* All the samples using CUDA Pipeline & Arrive-wait barriers are been updated to use new `cuda::pipeline` and `cuda::barrier` interfaces.
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* Updated all the samples to build with parallel build option `--threads` of `nvcc` cuda compiler.
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* Added `cudaNvSciNvMedia`. Demonstrates CUDA-NvMedia interop via NvSciBuf/NvSciSync APIs.
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* Added `simpleGL`. Demonstrates interoperability between CUDA and OpenGL.
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### CUDA 11.1
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* Added `watershedSegmentationNPP`. Demonstrates how to use the NPP watershed segmentation function.
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* 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.
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* Dropped Visual Studio 2012, 2013 support from all the windows supported samples.
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* Added kernel performing warp aggregated atomic max in multi buckets using cg::labeled_partition & cg::reduce in `warpAggregatedAtomicsCG`.
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* Added extended CG shuffle mechanics to `shfl_scan` sample.
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* Added `cudaOpenMP`. Demonstrates how to use OpenMP API to write an application for multiple GPUs.
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* Added `simpleZeroCopy`. Demonstrates how to use zero copy, kernels can read and write directly to pinned system memory.
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### CUDA 11.0
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* 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.
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* Added `bf16TensorCoreGemm`. Demonstrates __nv_bfloat16 (e8m7) GEMM computation using the __nv_bfloat16 WMMA API introduced with CUDA 11 in Ampere chip family tensor cores.
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* Added `tf32TensorCoreGemm`. Demonstrates tf32 (e8m10) GEMM computation using the tf32 WMMA API introduced with CUDA 11 in Ampere chip family tensor cores.
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* 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.
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* Added `simpleAWBarrier`. Demonstrates arrive wait barriers.
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* Added `simpleAttributes`. Demonstrates the stream attributes that affect L2 locality.
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* 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.
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* Added `binaryPartitionCG`. Demonstrates binary partition cooperative groups and reduction within the thread block.
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* 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.
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* Added `cudaCompressibleMemory`. Demonstrates compressible memory allocation using cuMemMap API.
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* Added `simpleVulkanMMAP`. Demonstrates Vulkan CUDA Interop via cuMemMap APIs.
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* Added `concurrentKernels`. Demonstrates the use of CUDA streams for concurrent execution of several kernels on a GPU.
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* Dropped Mac OSX support from all samples.
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### CUDA 10.2
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* Added `simpleD3D11`. Demonstrates CUDA-D3D11 External Resource Interoperability APIs for updating D3D11 buffers from CUDA and synchronization between D3D11 and CUDA with Keyed Mutexes.
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* Added `simpleDrvRuntime`. Demonstrates CUDA Driver and Runtime APIs working together to load fatbinary of a CUDA kernel.
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* 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.
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* Added `memMapIPCDrv`. Demonstrates Inter Process Communication using cuMemMap APIs.
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* Added `cudaNvSci`. Demonstrates CUDA-NvSciBuf/NvSciSync Interop.
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* Added `jacobiCudaGraphs`. Demonstrates Instantiated CUDA Graph Update with Jacobi Iterative Method using different approaches.
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* Added `cuSolverSp_LinearSolver`. Demonstrates cuSolverSP's LU, QR and Cholesky factorization.
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* Added `MersenneTwisterGP11213`. Demonstrates the Mersenne Twister random number generator GP11213 in cuRAND.
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### CUDA 10.1 Update 2
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* Added `vulkanImageCUDA`. Demonstrates how to perform Vulkan image - CUDA Interop.
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* Added `nvJPEG_encoder`. Demonstrates encoding of jpeg images using NVJPEG Library.
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* Added Windows OS support to `nvJPEG` sample.
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* Added `boxFilterNPP`. Demonstrates how to use NPP FilterBox function to perform a box filter.
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* Added `cannyEdgeDetectorNPP`. Demonstrates the nppiFilterCannyBorder_8u_C1R Canny Edge Detection image filter function.
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### CUDA 10.1 Update 1
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* Added `NV12toBGRandResize`. Demonstrates how to convert and resize NV12 frames to BGR planars frames using CUDA in batch.
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* Added `EGLStream_CUDA_Interop`. Demonstrates data exchange between CUDA and EGL Streams.
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* Added `cuSolverDn_LinearSolver`. Demonstrates cuSolverDN's LU, QR and Cholesky factorization.
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* Added support of Visual Studio 2019 to all samples supported on [Windows](./README.md#windows-1).
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### CUDA 10.1
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* Added `immaTensorCoreGemm`. Demonstrates integer GEMM computation using the Warp Matrix Multiply and Accumulate (WMMA) API for integers employing the Tensor Cores.
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* Added `simpleIPC`. Demonstrates Inter Process Communication with one process per GPU for computation.
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* Added `nvJPEG`. Demonstrates single and batched decoding of jpeg images using NVJPEG Library.
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* Added `bandwidthTest`. It measures the memcopy bandwidth of the GPU and memcpy bandwidth across PCI-e.
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* Added `reduction`. Demonstrates several important optimization strategies for Data-Parallel Algorithms like reduction.
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* Update all the samples to support CUDA 10.1.
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### CUDA 10.0
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* Added `simpleCudaGraphs`. Demonstrates CUDA Graphs creation, instantiation and launch using Graphs APIs and Stream Capture APIs.
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* Added `conjugateGradientCudaGraphs`. Demonstrates conjugate gradient solver on GPU using CUBLAS and CUSPARSE library calls captured and called using CUDA Graph APIs.
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* Added `simpleVulkan`. Demonstrates Vulkan - CUDA Interop.
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* Added `simpleD3D12`. Demonstrates DX12 - CUDA Interop.
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* Added `UnifiedMemoryPerf`. Demonstrates performance comparision of various memory types involved in system.
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* Added `p2pBandwidthLatencyTest`. Demonstrates Peer-To-Peer (P2P) data transfers between pairs of GPUs and computes latency and bandwidth.
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* Added `systemWideAtomics`. Demonstrates system wide atomic instructions.
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* Added `simpleCUBLASXT`. Demonstrates CUBLAS-XT library which performs GEMM operations over multiple GPUs.
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* Added Windows OS support to `conjugateGradientMultiDeviceCG` sample.
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* Removed support of Visual Studio 2010 from all samples.
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### CUDA 9.2
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This is the first release of CUDA Samples on GitHub:
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* Added `vectorAdd_nvrtc`. Demonstrates runtime compilation library using NVRTC of a simple vectorAdd kernel.
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* Added `warpAggregatedAtomicsCG`. Demonstrates warp aggregated atomics using Cooperative Groups.
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* Added `deviceQuery`. Enumerates the properties of the CUDA devices present in the system.
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* Added `matrixMul`. Demonstrates a matrix multiplication using shared memory through tiled approach.
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* Added `matrixMulDrv`. Demonstrates a matrix multiplication using shared memory through tiled approach, uses CUDA Driver API.
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* 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.
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* Added `simpleVoteIntrinsics` which uses *_sync equivalent of the vote intrinsics _any, _all added since CUDA 9.0.
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* Added `shfl_scan` which uses *_sync equivalent of the shfl intrinsics added since CUDA 9.0.
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* Added `conjugateGradientMultiBlockCG`. Demonstrates a conjugate gradient solver on GPU using Multi Block Cooperative Groups.
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* Added `conjugateGradientMultiDeviceCG`. Demonstrates a conjugate gradient solver on multiple GPUs using Multi Device Cooperative Groups, also uses unified memory prefetching and usage hints APIs.
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* Added `simpleCUBLAS`. Demonstrates how perform GEMM operations using CUBLAS library.
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* Added `simpleCUFFT`. Demonstrates how perform FFT operations using CUFFT library.
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