wangsiping97 / FastGEMV
High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.
☆87Updated 3 months ago
Related projects ⓘ
Alternatives and complementary repositories for FastGEMV
- ☆162Updated 3 months ago
- llama INT4 cuda inference with AWQ☆47Updated 4 months ago
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆196Updated last week
- Standalone Flash Attention v2 kernel without libtorch dependency☆98Updated last month
- PyTorch bindings for CUTLASS grouped GEMM.☆51Updated last week
- ☆79Updated 2 months ago
- Simple and fast low-bit matmul kernels in CUDA / Triton☆133Updated this week
- Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.☆48Updated 2 months ago
- A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer☆85Updated 8 months ago
- ☆156Updated last year
- Applied AI experiments and examples for PyTorch☆159Updated last week
- TiledCUDA is a highly efficient kernel template library designed to elevate CUDA C’s level of abstraction for processing tiles.☆148Updated this week
- Performance of the C++ interface of flash attention and flash attention v2 in large language model (LLM) inference scenarios.☆26Updated 2 months ago
- ☆45Updated last month
- ☆43Updated this week
- ☆121Updated this week
- A fast communication-overlapping library for tensor parallelism on GPUs.☆217Updated last week
- QQQ is an innovative and hardware-optimized W4A8 quantization solution for LLMs.☆75Updated 3 weeks ago
- ☆130Updated 3 months ago
- ☆47Updated 2 weeks ago
- Dynamic Memory Management for Serving LLMs without PagedAttention☆222Updated this week
- extensible collectives library in triton☆61Updated last month
- ☆88Updated 2 months ago
- Benchmark code for the "Online normalizer calculation for softmax" paper☆59Updated 6 years ago
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆277Updated 4 months ago
- ☆55Updated 5 months ago
- A Easy-to-understand TensorOp Matmul Tutorial☆287Updated last month
- Fast Matrix Multiplications for Lookup Table-Quantized LLMs☆183Updated last month
- Official PyTorch implementation of FlatQuant: Flatness Matters for LLM Quantization☆57Updated this week
- Fast Hadamard transform in CUDA, with a PyTorch interface☆107Updated 5 months ago