hclhkbu / gcoospdm
Sparse-dense matrix-matrix multiplication on GPUs
☆14Updated 6 years ago
Related projects ⓘ
Alternatives and complementary repositories for gcoospdm
- Escoin: Efficient Sparse Convolutional Neural Network Inference on GPUs☆15Updated 5 years ago
- Repository holding the code base to AC-SpGEMM : "Adaptive Sparse Matrix-Matrix Multiplication on the GPU"☆28Updated 4 years ago
- Code for paper "Design Principles for Sparse Matrix Multiplication on the GPU" accepted to Euro-Par 2018☆71Updated 4 years ago
- Efficient SpGEMM on GPU using CUDA and CSR☆50Updated last year
- BGHT: High-performance static GPU hash tables.☆55Updated 2 months ago
- CSR-based SpGEMM on nVidia and AMD GPUs☆45Updated 8 years ago
- This is a tuned sparse matrix dense vector multiplication(SpMV) library☆21Updated 8 years ago
- ☆38Updated 4 years ago
- Implementation of TSM2L and TSM2R -- High-Performance Tall-and-Skinny Matrix-Matrix Multiplication Algorithms for CUDA☆31Updated 4 years ago
- ☆90Updated 7 years ago
- A GPU algorithm for sparse matrix-matrix multiplication☆66Updated 4 years ago
- Benchmark for matrix multiplications between dense and block sparse (BSR) matrix in TVM, blocksparse (Gray et al.) and cuSparse.☆24Updated 4 years ago
- Sparse matrix computation library for GPU☆54Updated 4 years ago
- TTC: A high-performance Compiler for Tensor Transpositions☆20Updated 7 years ago
- study of Ampere' Sparse Matmul☆14Updated 3 years ago
- A Winograd Minimal Filter Implementation in CUDA☆23Updated 3 years ago
- Sparse matrix-matrix multiplication on CPU+GPU systems.☆13Updated 10 years ago
- An extension library of WMMA API (Tensor Core API)☆84Updated 4 months ago
- ☆80Updated 7 months ago
- New batched algorithm for sparse matrix-matrix multiplication (SpMM)☆16Updated 5 years ago
- CUDA Flux is a profiler for GPU applications which reports the basic block executions frequencies of compute kernels☆31Updated 3 years ago
- flexible-gemm conv of deepcore☆17Updated 4 years ago
- Evaluating different memory managers for dynamic GPU memory☆24Updated 3 years ago
- Use tensor core to calculate back-to-back HGEMM (half-precision general matrix multiplication) with MMA PTX instruction.☆11Updated last year
- Magicube is a high-performance library for quantized sparse matrix operations (SpMM and SDDMM) of deep learning on Tensor Cores.☆81Updated last year
- ☆10Updated 4 years ago
- ☆15Updated 5 years ago
- ☆17Updated 4 years ago
- ☆20Updated 2 years ago
- Matrix Multiply-Accumulate with CUDA and WMMA( Tensor Core)☆116Updated 4 years ago