cTuning foundation (a founding member of MLCommons and ACM taskforce on reproducibility)
- Paris, France
- https://cTuning.org
- @grigori_fursin
- admin@cTuning.org
Pinned repositories
Repositories
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ck
Collective Knowledge framework (CK) helps to organize software projects as a database of reusable components, automation recipes and portable workflows with common APIs and extensible meta descriptions based on FAIR principles. See the real-world use cases to support reproducible MLSys R&D, enable portable MLOps and automate ML/SW/HW co-design:
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ck-mlops
A collection of portable workflows, automation recipes and components for MLOps in a unified CK format with a common CLI, Python API, extensible meta descriptions and web services. See real world use cases to co-design, benchmark and deploy efficient ML Systems from MLCommons/MLPerf, Qualcomm, Arm, GM, the Raspberry Pi foundation, ACM and others:
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ck-ml-min
minimal CK components for ML
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ck-mlperf-inference
CK automation recipes for the MLPerf inference benchmark:
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reproduce-pamela-project-small-dataset
Medium data set (20 frames) in the CK format for the EPSRC Pamela project:
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reproduce-pamela-project
Shared artifacts and workflows from the EPSRC Pamela project in the customizable, portable and reusable Collective Knowledge format:
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reproduce-milepost-project
Collective Knowledge workflow for the MILEPOST GCC (machine learning based compiler). See how it is used in the collaborative project with the Raspberry Pi foundation to support collaborative research for multi-objective autotuning and machine learning techniques, and prototype reproducible papers with portable workflows:
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reproduce-ck-paper
Shared artifacts in the Collective Knowledge Format as a proof-of-concept to reproduce our recent Collective Mind- and Collective Knowledge-related papers
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reproduce-carp-project
Shared artifacts and workflows from the EU FP7 Carp project in the customizable, portable and reusable Collective Knowledge format:
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reproduce-adapt16
Reproducing ADAPT'16 paper
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ctuning-programs
Collective Knowledge extension with unified and customizable benchmarks (with extensible JSON meta information) to be easily integrated with customizable and portable Collective Knowledge workflows. You can easily compile and run these benchmarks using different compilers, environments, hardware and OS (Linux, MacOS, Windows, Android). More info:
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ctuning-datasets-min
Public data sets and their properties in the Collective Knowledge Format with JSON API and JSON meta information to be easily pluggable to customizable and reproducible CK experimental workflows (such as collaborative program analysis and optimization):
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ck-web
Collective Knowledge web extension to browse CK repositories, visualize interactive graphs and articles, render CK-based websites, implement simple web services with JSON API (for example to crowdsource experiments or unify access to DNN). Demos of interactive articles, graphs and crowdsourced experiments:
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ck-wa
Collective Knowledge workflow for ARM's workload automation tool: an open framework for gathering and sharing knowledge about system design and optimization using real-world workloads.
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ck-tvm
Portable and customizable Collective Knowledge workflows for TVM and VTA:
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ck-tensorrt
Collective Knowledge repository for NVIDIA's TensorRT
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ck-tensorflow
Collective Knowledge components for TensorFlow (code, data sets, models, packages, workflows):
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ck-tbd-suite
Prototyping CK workflows for ML training
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ck-scc18
Beta Collective Knowledge workflow to automate installation, execution, customization and validation of SeisSol application from the SCC18 Reproducibility Challenge across different platforms and environments:
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ck-scc
The procedures and a workflow to prepare Student Cluster Competition submissions:
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ck-rigetti
CK repository for Rigetti Computing workflows
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ck-quantum
Miscellaneous resources for Quantum Collective Knowledge
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ck-qiskit
CK repository for Quantum Information Software Kit (QISKit)
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ck-pytorch
Integration of PyTorch to Collective Knowledge workflow framework to provide unified CK JSON API for AI (customized builds across diverse libraries and hardware, unified AI API, collaborative experiments, performance optimization and model/data set tuning):
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ck-openvino
Collective Knowledge workflows for OpenVINO Toolkit (Deep Learning Deployment Toolkit)
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ck-object-detection
CK research workflows for object detection
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ck-nntest
CK-NNTest: collaboratively validating, benchmarking and optimizing neural net operators across platforms, frameworks and datasets
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ck-mxnet
Portable and customizable Collective Knowledge workflows for MXNet:
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ck-mvnc
Collective Knowledge Workflows for Movidius Neural Compute Stick as a part of AI unification:
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ck-mlperf
Collective Knowledge repository to automate MLPerf - a broad ML benchmark suite for measuring performance of ML software frameworks, ML hardware accelerators, and ML cloud platforms:
