MOTrainer
MOTrainer: Distributed Measurement Operator Trainer for Data Assimilation Applications - Published in JOSS (2024)
Mango.jl
Mango.jl: A Julia-Based Multi-Agent Simulation Framework - Published in JOSS (2024)
dsBinVal
dsBinVal: Conducting distributed ROC analysis using DataSHIELD - Published in JOSS (2023)
https://github.com/hpcaitech/colossalai
Making large AI models cheaper, faster and more accessible
alchemiscale
a high-throughput alchemical free energy execution system for use with HPC, cloud, bare metal, and Folding@Home
pennylane-lightning
The Lightning plugin ecosystem provides fast quantum state-vector and tensor network simulators written in C++ for use with PennyLane.
torchrl
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
wrapyfi
Robotics MOM and RPC middleware wrapper with deep-learning framework integration
catalyst
Accelerated deep learning R&D
compss
COMP Superscalar (COMPSs) is a framework which aims to ease the development and execution of applications for distributed infrastructures, such as Clusters, Grids and Clouds.
pyscreener
pyscreener: A Python Wrapper for Computational Docking Software - Published in JOSS (2022)
yggdrasil-decision-forests
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
rockyml
⛰️ RockyML - A High-Performance Scientific Computing Framework for Non-smooth Machine Learning Problems
cato
Automatic source transformation to apply HPC frameworks with minimal user interaction
persia
High performance distributed framework for training deep learning recommendation models based on PyTorch.
https://github.com/lablup/backend.ai
Backend.AI is a streamlined, container-based computing cluster platform that hosts popular computing/ML frameworks and diverse programming languages, with pluggable heterogeneous accelerator support including CUDA GPU, ROCm GPU, TPU, IPU and other NPUs.
future
:rocket: R package: future: Unified Parallel and Distributed Processing in R for Everyone
https://github.com/agnostiqhq/covalent-ssh-plugin
Executor plugin interfacing Covalent with remote backends using SSH
fugue
A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
https://github.com/futureverse/future.apply
:rocket: R package: future.apply - Apply Function to Elements in Parallel using Futures
pararealgpu.jl
A distributed and GPU-based implementation of the Parareal algorithm for parallel-in-time integration of equations of motion.
https://github.com/cubed-dev/cubed
Scalable array processing with bounded memory
doFuture
:rocket: R package: doFuture - Use Foreach to Parallelize via Future Framework
https://github.com/futureverse/future.batchtools
:rocket: R package future.batchtools: A Future API for Parallel and Distributed Processing using batchtools
https://github.com/bsc-wdc/dislib
The Distributed Computing library for python implemented using PyCOMPSs programming model for HPC.
https://github.com/dmetivie/robust-randomized-quasi-monte-carlo-paper-code
Code of the paper The Robust Randomized Quasi Monte Carlo method, applications to integrating singular functions by E. Gobet M. Lerasle and D. Métivier
https://github.com/alpa-projects/alpa
Training and serving large-scale neural networks with auto parallelization.
https://github.com/cdpxe/nefias
Network Forensic & Anomaly Detection System; tailored for covert channel/network steganography detection
https://github.com/agnostiqhq/tutorials_covalent_mlops_2022
Covalent tutorial for MLOps 2022
https://github.com/darma-tasking/lb-analysis-framework
Analysis framework for exploring, testing, and comparing load balancing strategies
https://github.com/paganini2008/vortex-tsdb
Vortex is a cutting-edge time series database (TSDB) framework designed for precision, scalability, and real-time data analytics. Built on Spring Cloud, it supports fine-grained data storage with a 1-minute resolution
https://github.com/constraintautomaton/introducing-collaborative-link-traversal-query-processing
Doctoral project proposal where I introduce Collaborative Link Data Query Processing, a paradigm where multiple query engines collaborate to improve query completeness and execution time in Link Traversal Query Processing
trustmesh
TrustMesh is a blockchain-enabled distributed computing framework designed for trustless heterogeneous IoT environments
delicoco-ieee-transactions
In compressed decentralized optimization settings, there are benefits to having multiple gossip steps between subsequent gradient iterations, even when the cost of doing so is appropriately accounted for e.g. by means of reducing the precision of compressed information.
https://github.com/hypershell/hypershell
Cross-platform, high-throughput computing utility for processing shell commands over a distributed, asynchronous queue.
https://github.com/appfl/fedcompass
[ICLR 2024] FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler
p3d-dfs
Set of parallel Branch-and-Bound skeletons in Chapel targeting CPU-based systems at every scale.
spark-dynamic-executor-time-prediction
Neural Network Models for Predicting Execution Time with Dynamic Executor Allocation in Apache Spark.
alchemiscale-fah
protocols and compute service for using alchemiscale with Folding@Home
hybridsim
A graphical simulator for the two-dimensional hybrid model of programmable matter.
https://github.com/charmplusplus/charm4py
Parallel Programming with Python and Charm++