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Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory…
[MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".
SGLang is a fast serving framework for large language models and vision language models.
Applied AI experiments and examples for PyTorch
Simple go utility to download HuggingFace Models and Datasets
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
A gem5 experimental repo in order to explore Data-dependent Access (DDA).
Fast and accurate DRAM power and energy estimation tool
Ramulator 2.0 is a modern, modular, extensible, and fast cycle-accurate DRAM simulator. It provides support for agile implementation and evaluation of new memory system designs (e.g., new DRAM stan…
A Fast and Extensible DRAM Simulator, with built-in support for modeling many different DRAM technologies including DDRx, LPDDRx, GDDRx, WIOx, HBMx, and various academic proposals. Described in the…
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Portable header-only C++ low level SIMD library
Agenium Scale vectorization library for CPUs and GPUs