dividiti's Repositories

Collective Knowledge (CK) is a small Python library that helps to decompose complex research projects into reusable and cross-linked components (wrappers for code, data, models and results), automation actions and portable workflows with unified APIs, CLI, and JSON I/O. You can find more info and real-world use cases at the project website:

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Collective Knowledge repository with actions to unify the access to different predictive analytics engines (scipy, R, DNN) from software, command line and web-services via CK JSON API:

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Collective Knowledge workflows for ArmNN

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CK automation actions to let users implement portable, customizable and reusable program workflows for reproducible, collaborative and multi-objective benchmarking, optimization and SW/HW co-design:

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Collective Knowledge workflow for Caffe to automate installation across diverse platforms and to collaboratively evaluate and optimize Caffe-based workloads across diverse hardware, software and data sets (compilers, libraries, tools, models, inputs):

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ck-caffe-explore-batch-size-chromebook2

CK-Caffe performance experiments on Samsung Chromebook 2

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ck-caffe-firefly-rk3399

CK-Caffe public benchmarking data on Firefly-RK3399

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ck-caffe-nvidia-gtx1080

CK-Caffe public benchmarking data on NVIDIA GTX1080

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ck-caffe-nvidia-tx1

CK-Caffe public benchmarking data on NVIDIA TX1

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ck-caffe-samsung-chromebook2

CK-Caffe public benchmarking data on Samsung Chromebook 2

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Integration of Caffe2 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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Collective Knowledge extension to crowdsource bug detection in OpenCL compilers using CLSmith tool from Imperial College London

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Collective Knowledge workflows for the Coral EdgeTPU accelerator

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ck-crowd-scenarios

Public scenarios to crowdsource experiments (such as DNN crowd-benchmarking and crowd-tuning) using Collective Knowledge Framework across diverse mobile devices provided by volunteers. Results are continuously aggregated at the open repository of knowledge:

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ck-crowdsource-dnn-optimization

CK GUI application to crowdsource benchmarking and optimization of DNN engines and models across diverse Linux or Windows platforms. Further info:

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Collective Knowledge crowd-tuning extension to let users crowdsource their experiments (using portable Collective Knowledge workflows) such as performance benchmarking, auto tuning and machine learning across diverse platforms with Linux, Windows, MacOS and Android provided by volunteers. Demo of DNN crowd-benchmarking and crowd-tuning:

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ck-crowdtuning-platforms

Meta information about platforms participating in experiment crowdsourcing using Collective Knowledge Framework (OS,CPU,GPU,GPGPU,NN...):

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ck-dev-compilers

Collective Knowledge packages to build development versions of compilers (LLVM, GCC, etc) and use them in customizable and portable CK research workflows:

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CK dev private repo

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Collective Knowledge workflows for DeePhi's DNNDK

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Collective Knowledge extension to automate Docker "build","run" and "push" functions and packge CK repositories for collaborative and reproducible research:

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CK workflows for the eHive project

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CK repository with components and automation actions to enable portable workflows across diverse platforms including Linux, Windows, MacOS and Android. It includes software detection plugins and meta packages (code, data sets, models, scripts, etc) with the possibility of multiple versions to co-exist in a user or system environment:

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ck-graph-analytics

Collective Knowledge repository with workflows and packages for graph analytics applications

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Collective Knowledge repository for Kalray's KaNN

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Collective Knowledge packages for various mathematical libs to be plugged into portable and customizable CK research workflows:

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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:

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

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ck-nntest-outputs

Reference outputs for nntest

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ck-object-detection

CK research workflows for object detection

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ck-old-packages

Collective Knowledge repository to archive outdated packages

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

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CK repository for ProjectQ

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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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Miscellaneous resources for Quantum Collective Knowledge

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Collective Knowledge workflows to support ReQuEST tournaments (open, reproducible and Pareto-efficient SW/HW co-design of emerging workloads such as deep learning):

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ck-request-asplos18-caffe-intel

CK workflow, portable packages and other artifacts for the ReQuEST-ASPLOS'18 submission:

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ck-request-asplos18-mobilenets-armcl-opencl

CK workflow, portable packages and other artifacts for the ReQuEST-ASPLOS'18 submission:

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CK repository for Rigetti Computing workflows

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ck-rpi-optimization

CK repository to collaboratively optimize benchmarks, kernels and realistic workloads across Raspberry Pi devices provided by volunteers (starting from compiler flag autotuning). Interactive article with all results:

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Collective Knowledge components for TensorFlow (code, data sets, models, packages, workflows):

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Collective Knowledge repository for NVIDIA's TensorRT

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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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Extra resources in the Collective Knowledge Format for ARM's Workload Automation Framework:

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ck-wa-workloads

ARM's workloads in the universal Collective Knowledge Format with JSON API and JSON meta information to power Workload Automation Framework

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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 repository for cKnowledge.org website:

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CK repository for experiments with ZeroMQ, LoadGen and TensorRT

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Tuned OpenCL BLAS

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The ARM Computer Vision and Machine Learning library is a set of functions optimised for both ARM CPUs and GPUs using SIMD technologies.

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crowdsource-experiments-using-android-devices

Android application to participate in experiment crowdsourcing (such as workload crowd-benchmarking and crowd-tuning) using Collective Knowledge Framework and open repositories of knowledge:

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crowdsource-video-experiments-on-android

Crowdsourcing video experiments (such as collaborative benchmarking and optimization of DNN algorithms) using Collective Knowledge Framework across diverse Android devices provided by volunteers. Results are continuously aggregated in the open repository:

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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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ctuning-modules

cTuning modules

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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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dividiti's OpenCL API profiler

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Benchmark for generic matrix-matrix multiplication (GEMM)

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gemmbench-adapt16

Shared experiments for the ADAPT'16 submission on GEMMbench

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Reference implementations of inference benchmarks

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inference_policies

Please use for issues related to inference policies, including suggested changes

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inference_results_v0.5

MLPerf Inference v0.5 Results

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inference_results_v0.7

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jetson-inference

Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and Jetson TX1.

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Simple plugin and event-based interface to expose externals of hardwired tools (and connect them to Collective Knowledge Framework). Further info:

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pencil-benchmark

An extended benchmark for polyhedral compilers

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General policies

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shader-compiler-bugs

A collection of shader compiler bugs.

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A tensorflow implementation for SqueezeDet, a convolutional neural network for object detection.

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Developer repository for ViennaCL. Visit http://viennacl.sourceforge.net/ for the latest releases.

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