Running large language models on a single GPU for throughput-oriented scenarios.
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Updated
Jul 24, 2024 - Python
Running large language models on a single GPU for throughput-oriented scenarios.
A thread-safe queue faster and more resource efficient than golang's native channels
Time series monitoring and alerting platform.
Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)
[NeurIPS'23] H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.
quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.
atomate2 is a library of computational materials science workflows
extremly light uart library for AVR 8 bit microcontrollers
A low-latency LRU approximation cache in C++ using CLOCK second-chance algorithm. Multi level cache too. Up to 2.5 billion lookups per second.
An Intuitive, Lightweight, High Performance Full Stack Java Web Framework.
A reactive driver for Aeron transport (https://github.com/real-logic/aeron)
A Simple Way of Creating Job Workflows in Go running in Processes, Containers, Tasks, Pods, or Jobs
Full automation of relative protein-ligand binding free energy calculations in GROMACS
Window-Based Hybrid CPU/GPU Stream Processing Engine
🔬🖥 Automated Blood Vasculature Analysis of 3D Light-Sheet Image Volumes
The Zavolab Automated RNA-seq Pipeline
A low-latency, high-throughput order matching system implementation.
High-throughput molecular docking with multiple targets and ligands using Vina series engines
MatID is a python package for identifying and analyzing atomistic systems based on their structure. MatID is designed to help researchers in the automated analysis and labeling of atomistic datasets.
Post-processing toolkit for electronic structure calculations
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