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Grigori Fursin's Projects

aggregathor icon aggregathor

Byzantine-resilient distributed SGD with TensorFlow.

browser-extension-for-reproducible-research icon browser-extension-for-reproducible-research

Browser extension for Chrome and FireFox to collaboratively annotate web pages with related research papers, code, reproducible results, scoreboards, portable workflows and reusable artifacts.

caffe2 icon caffe2

Caffe2 is a lightweight, modular, and scalable deep learning framework.

cbase icon cbase

Collective Knowledge DataBase

ck icon ck

Collective Knowledge framework (CK) helps to organize any software project as a database of reusable components and micro-services with common APIs, automation actions and extensible meta descriptions. See real-world use cases from MLPerf, Arm, General Motors, IBM, Raspberry Pi and ACM:

ck-autotuning icon ck-autotuning

Collective Knowledge extension to let users implement customizable, portable, multi-dimensional and multi-objective SW/HW auto-tuning workflows using Collective Knowledge Framework. It is used as a universal engine for collaborative AI crowd-benchmarking and crowd-tuning across different compilers, libraries, run-time systems and platforms:

ck-nntest icon ck-nntest

CK-NNTest: collaboratively validating, benchmarking and optimizing neural net operators across platforms, frameworks and datasets

ck-openvino icon ck-openvino

Collective Knowledge workflows for OpenVINO Toolkit (Deep Learning Deployment Toolkit)

cm4mlops icon cm4mlops

A collection of reusable and cross-platform automation recipes (CM scripts) with a human-friendly interface and minimal dependencies to make it easier to compose, benchmark and optimize AI, ML and other applications and systems across diverse and continuously changing models, data sets, software and hardware (cloud/edge)

compilergym icon compilergym

A reinforcement learning toolkit for compiler optimizations

gym icon gym

A toolkit for developing and comparing reinforcement learning algorithms.

inference icon inference

Reference implementations of MLPerf™ inference benchmarks

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