Pinned Repositories
aimet
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
bitstarter
ck
CK framework helps to share artifacts, knowledge and experience in a more reusable, automated, portable, reproducible and unified way. It transforms Git repositories, Docker containers, Jupyter notebooks and zip/tar files into an open database of reusable artifacts and automations with a unified API and extensible meta descriptions.
ck-math
Collective Knowledge packages for various mathematical libs to be plugged into portable and customizable CK research workflows:
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 automate ML/SW/HW co-design and make it easier to deploy efficient ML Systems across diverse platforms:
ck-qaic
Qualcomm Cloud AI (QAIC) implementation of MLPerf Inference benchmarks
ck_mlperf_results
Aggregated benchmarking results from MLPerf Inference, Tiny and Training in the MLCommons CM format for the Collective Knowledge Playground. Our goal is to make it easier for the community to visualize, compare and reproduce MLPerf results and add derived metrics such as Performance/Watt or Performance/$
cm4abtf
CM interface and automation recipes for ABTF
cm4mlops_clean_history
cm4mlperf-inference
arjunsuresh's Repositories
arjunsuresh/cm4mlperf-inference
arjunsuresh/ck
CK framework helps to share artifacts, knowledge and experience in a more reusable, automated, portable, reproducible and unified way. It transforms Git repositories, Docker containers, Jupyter notebooks and zip/tar files into an open database of reusable artifacts and automations with a unified API and extensible meta descriptions.
arjunsuresh/ck-math
Collective Knowledge packages for various mathematical libs to be plugged into portable and customizable CK research workflows:
arjunsuresh/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 automate ML/SW/HW co-design and make it easier to deploy efficient ML Systems across diverse platforms:
arjunsuresh/ck-qaic
Qualcomm Cloud AI (QAIC) implementation of MLPerf Inference benchmarks
arjunsuresh/ck_mlperf_results
Aggregated benchmarking results from MLPerf Inference, Tiny and Training in the MLCommons CM format for the Collective Knowledge Playground. Our goal is to make it easier for the community to visualize, compare and reproduce MLPerf results and add derived metrics such as Performance/Watt or Performance/$
arjunsuresh/cm4abtf
CM interface and automation recipes for ABTF
arjunsuresh/cm4mlops_clean_history
arjunsuresh/cocoapi
COCO API - Dataset @ http://cocodataset.org/
arjunsuresh/DALI_deps
3rd party dependencies for DALI project
arjunsuresh/inference
Reference implementations of MLPerf™ inference benchmarks
arjunsuresh/inference_policies
Issues related to MLPerf™ Inference policies, including rules and suggested changes
arjunsuresh/inference_results_v2.1
arjunsuresh/inference_results_v1.1
arjunsuresh/inference_results_v3.0
arjunsuresh/inference_results_v3.1
This repository contains the results and code for the MLPerf™ Inference v3.1 benchmark.
arjunsuresh/logging
MLPerf™ logging library
arjunsuresh/mlcommons-inference
Fork of MLCommons inference repository to test TVM integration
arjunsuresh/mlperf-inference-configs
arjunsuresh/mlperf_inference_submissions_v3.0
arjunsuresh/mlperf_inference_submissions_v3.0-1
MLPerf inference submissions v3.0 playground
arjunsuresh/mlperf_inference_v4.0
arjunsuresh/onnx-mlir
Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure
arjunsuresh/policies
General policies for MLPerf™ including submission rules, coding standards, etc.
arjunsuresh/power-dev
Dev repo for power measurement for the MLPerf™ benchmarks
arjunsuresh/q2a-book
Allows book export for Question2Answer
arjunsuresh/software-kit-for-qualcomm-cloud-ai-100
Software kit for Qualcomm Cloud AI 100
arjunsuresh/software-kit-for-qualcomm-cloud-ai-100-cc
Software kit for Qualcomm Cloud AI 100 cc
arjunsuresh/tpu
Reference models and tools for Cloud TPUs.
arjunsuresh/training
Reference implementations of MLPerf™ training benchmarks