Fast inference engine for Transformer models
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Updated
May 20, 2024 - C++
Fast inference engine for Transformer models
Tuned OpenCL BLAS
🎉CUDA 笔记 / 大模型手撕CUDA / C++笔记,更新随缘: flash_attn、sgemm、sgemv、warp reduce、block reduce、dot product、elementwise、softmax、layernorm、rmsnorm、hist etc.
BLISlab: A Sandbox for Optimizing GEMM
The HPC toolbox: fused matrix multiplication, convolution, data-parallel strided tensor primitives, OpenMP facilities, SIMD, JIT Assembler, CPU detection, state-of-the-art vectorized BLAS for floats and integers
Optimizing SGEMM kernel functions on NVIDIA GPUs to a close-to-cuBLAS performance.
Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.
Stretching GPU performance for GEMMs and tensor contractions.
DBCSR: Distributed Block Compressed Sparse Row matrix library
FP64 equivalent GEMM via Int8 Tensor Cores using the Ozaki scheme
hipBLASLt is a library that provides general matrix-matrix operations with a flexible API and extends functionalities beyond a traditional BLAS library
Serial and parallel implementations of matrix multiplication
code for benchmarking GPU performance based on cublasSgemm and cublasHgemm
Specialized Parallel Linear Algebra, providing distributed GEMM functionality for specific matrix distributions with optional GPU acceleration.
The simplest but fast implementation of matrix multiplication in CUDA.
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