xnd-project / cuda-benchmarksLinks
Collection of CUDA benchmarks, with a focus on unified vs. explicit memory management.
☆20Updated 5 years ago
Alternatives and similar repositories for cuda-benchmarks
Users that are interested in cuda-benchmarks are comparing it to the libraries listed below
Sorting:
- a c++/cuda template library for tensor lazy evaluation☆163Updated 2 years ago
- Learning and practice of high performance computing (CUDA, Vulkan, OpenCL, OpenMP, TBB, SSE/AVX, NEON, MPI, coroutines, etc. )☆62Updated 6 months ago
- THIS REPOSITORY HAS MOVED TO github.com/nvidia/cub, WHICH IS AUTOMATICALLY MIRRORED HERE.☆84Updated last year
- Fast CUDA Kernels for ResNet Inference.☆180Updated 6 years ago
- tophub autotvm log collections☆69Updated 2 years ago
- CUDA Tensor Transpose (cuTT) library☆53Updated 8 years ago
- Benchmark of TVM quantized model on CUDA☆111Updated 5 years ago
- Learn OpenCL step by step.☆136Updated 3 years ago
- A GPU benchmark suite for assessing on-chip GPU memory bandwidth☆106Updated 8 years ago
- ☆44Updated 7 years ago
- Instructions, Docker images, and examples for Nsight Compute and Nsight Systems☆133Updated 5 years ago
- heterogeneity-aware-lowering-and-optimization☆256Updated last year
- flexible-gemm conv of deepcore☆17Updated 5 years ago
- CUDA implementation of the fundamental sum reduce operation. Aims to be as optimized as reasonable.☆39Updated 8 years ago
- clone of https://code.google.com/p/opencl-book-samples (there's an official repo here https://github.com/bgaster/opencl-book-samples)☆47Updated 12 years ago
- TVM stack: exploring the incredible explosion of deep-learning frameworks and how to bring them together☆64Updated 7 years ago
- ICML2017 MEC: Memory-efficient Convolution for Deep Neural Network C++实现(非官方)☆17Updated 6 years ago
- Winograd-based convolution implementation in OpenCL☆28Updated 8 years ago
- cuDNN sample codes provided by Nvidia☆46Updated 6 years ago
- portDNN is a library implementing neural network algorithms written using SYCL☆113Updated last year
- A tool for examining GPU scheduling behavior.☆88Updated last year
- Optimized half precision gemm assembly kernels (deprecated due to ROCm)☆47Updated 8 years ago
- TensorFlow and TVM integration☆36Updated 5 years ago
- Efficient Top-K implementation on the GPU☆188Updated 6 years ago
- Implementations of 2D Image Convolution algorithm with CUDA (using global memory, shared memory and constant memory)☆17Updated 7 years ago
- Example of how to use CUDA with CMake >= 3.8☆70Updated 4 months ago
- ☆69Updated 11 years ago
- Code for testing the native float16 matrix multiplication performance on Tesla P100 and V100 GPU based on cublasHgemm☆34Updated 6 years ago
- ☆26Updated 8 years ago
- Optimizing Mobile Deep Learning on ARM GPU with TVM☆181Updated 6 years ago