mlc-ai / mlc-enLinks
☆421Updated 8 months ago
Alternatives and similar repositories for mlc-en
Users that are interested in mlc-en are comparing it to the libraries listed below
Sorting:
- ☆206Updated 7 months ago
- An open-source efficient deep learning framework/compiler, written in python.☆707Updated 3 weeks ago
- Latency and Memory Analysis of Transformer Models for Training and Inference☆434Updated 2 months ago
- Fast low-bit matmul kernels in Triton☆327Updated this week
- A curated list of awesome projects and papers for distributed training or inference☆239Updated 9 months ago
- ☆225Updated this week
- Applied AI experiments and examples for PyTorch☆281Updated last month
- BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.☆643Updated this week
- Cataloging released Triton kernels.☆242Updated 6 months ago
- A library to analyze PyTorch traces.☆391Updated this week
- Shared Middle-Layer for Triton Compilation☆258Updated this week
- GPTQ inference Triton kernel☆302Updated 2 years ago
- Zero Bubble Pipeline Parallelism☆403Updated 2 months ago
- Perplexity GPU Kernels☆395Updated last month
- ☆195Updated 2 years ago
- [MLSys'25] QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving; [MLSys'25] LServe: Efficient Long-sequence LLM Se…☆714Updated 4 months ago
- ☆145Updated 5 months ago
- Distributed Compiler based on Triton for Parallel Systems☆870Updated last week
- Microsoft Automatic Mixed Precision Library☆612Updated 9 months ago
- Collection of kernels written in Triton language☆136Updated 3 months ago
- An experimental CPU backend for Triton☆134Updated last month
- ☆169Updated last year
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆313Updated last year
- A collection of memory efficient attention operators implemented in the Triton language.☆272Updated last year
- Dynamic Memory Management for Serving LLMs without PagedAttention☆401Updated last month
- FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.☆855Updated 10 months ago
- A Easy-to-understand TensorOp Matmul Tutorial☆365Updated 9 months ago
- ☆214Updated last year
- AI and Memory Wall☆217Updated last year
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆254Updated 8 months ago