tspeterkim / paged-attention-minimalLinks
a minimal cache manager for PagedAttention, on top of llama3.
☆125Updated last year
Alternatives and similar repositories for paged-attention-minimal
Users that are interested in paged-attention-minimal are comparing it to the libraries listed below
Sorting:
- Cataloging released Triton kernels.☆265Updated 2 months ago
- Fast low-bit matmul kernels in Triton☆392Updated 2 weeks ago
- Applied AI experiments and examples for PyTorch☆302Updated 2 months ago
- ☆246Updated this week
- Collection of kernels written in Triton language☆161Updated 7 months ago
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆242Updated 6 months ago
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆277Updated last week
- ring-attention experiments☆155Updated last year
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆216Updated last week
- ☆243Updated last year
- A minimal implementation of vllm.☆60Updated last year
- [ICLR'25] Fast Inference of MoE Models with CPU-GPU Orchestration☆240Updated 11 months ago
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆327Updated last year
- PyTorch bindings for CUTLASS grouped GEMM.☆126Updated 5 months ago
- Boosting 4-bit inference kernels with 2:4 Sparsity☆85Updated last year
- QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference☆118Updated last year
- ☆93Updated last year
- Fast Hadamard transform in CUDA, with a PyTorch interface☆255Updated 3 weeks ago
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆271Updated 3 months ago
- extensible collectives library in triton☆90Updated 7 months ago
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆120Updated last year
- Fastest kernels written from scratch☆386Updated last month
- Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity☆222Updated 2 years ago
- Dynamic Memory Management for Serving LLMs without PagedAttention☆434Updated 5 months ago
- A bunch of kernels that might make stuff slower 😉☆64Updated this week
- ☆83Updated 9 months ago
- Triton-based implementation of Sparse Mixture of Experts.☆248Updated last month
- QuTLASS: CUTLASS-Powered Quantized BLAS for Deep Learning☆128Updated last week
- kernels, of the mega variety☆597Updated last month
- Utility scripts for PyTorch (e.g. Make Perfetto show some disappearing kernels, Memory profiler that understands more low-level allocatio…☆64Updated 2 months ago