Hpc-Ops

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hpc-ops is an AI Agents & Automation tool that provides a high-performance operator library for LLM inference. It offers deeply optimized kernels for NVIDIA H20 GPUs, delivering significant speedups for large-scale production inference.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is hpc-ops?

HPC-Ops is a production-grade, high-performance, and easy-to-use operator library specifically designed for Large Language Model (LLM) inference. Developed by the Tencent Hunyuan AI Infra team, it features deeply optimized kernels tailored for NVIDIA H20 GPUs, achieving up to 2.22x speedup compared to baselines. This library is proven in large-scale production inference within Tencent and offers a clean API for seamless integration into popular inference frameworks like vLLM and SGLang. It supports multiple data types, including BF16 and FP8 with various quantization schemes, and provides hands-on examples for building state-of-the-art kernels using CuTe and CUTLASS.

Best used for

Ideal for developers and data scientists who need to significantly accelerate LLM inference, integrate highly optimized kernels into existing frameworks like vLLM, and leverage advanced precision support for efficient model deployment. Especially valuable for those working with NVIDIA H20 GPUs and requiring production-grade performance.

Common actions

optimize LLM inference

integrate AI kernels

accelerate deep learning

develop high-performance operators

deepfakeopen-sourceworkflowslow-code/no-codegithub copilot"AI Agents"face swappingautomated workflowcollaboration

Capabilities

Key features

SOTA performance
Production-proven kernels
Easy API integration
Rich precision support
CUDA tutorial examples
Optimized attention kernels
Quantized Grouped GEMM

Target Audience

developerdata scientist

Integrations

vllmsglang

Pricing & Plans

Open Source

Free

FAQs

What hardware is required to use HPC-Ops?

HPC-Ops requires an NVIDIA SM90 architecture GPU, which includes GPUs like the H20. It also needs Python 3.8 or higher, C++17 compatible compilers, and CUDA Toolkit 12.8 or higher for optimal performance and functionality.

Can HPC-Ops be integrated with existing LLM inference frameworks?

Yes, HPC-Ops is designed with a clean API for seamless integration into popular LLM inference frameworks. Examples include vLLM and SGLang, allowing developers to easily incorporate its optimized kernels into their current setups.

What kind of performance improvements can be expected with HPC-Ops?

HPC-Ops delivers significant performance improvements, with observed speedups up to 2.22x for attention operations and 1.88x for GroupGEMM, compared to various baselines. These optimizations are particularly effective for NVIDIA H20 GPUs.

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