https://bitbucket.org/Aratz/orchestral
공식 코드Orchestral: a lightweight framework for parallel simulations of cell-cell communication
Papers with Code 아카이브
Distributed Computing
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/APE-group/201812RealTimeCortSim
공식 코드Real-time cortical simulations: energy and interconnect scaling on distributed systems
https://github.com/ARM-software/mango
공식 코드https://github.com/AlfredsLapkovskis/SmartVideoStream
공식 코드Benchmarking Dynamic SLO Compliance in Distributed Computing Continuum Systems
https://github.com/AlfredsLapkovskis/VideoStreamEnv
공식 코드Benchmarking Dynamic SLO Compliance in Distributed Computing Continuum Systems
https://github.com/Azure/mmlspark
공식 코드https://github.com/Hao840/MAHPPO
공식 코드https://github.com/LiuHaiTao01/GRBCM
공식 코드Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression
https://github.com/MozartZheng/DistributedBA
공식 코드https://github.com/OptMLGroup/SQN
공식 코드Quasi-Newton Methods for Machine Learning: Forget the Past, Just Sample
https://github.com/PaddlePaddle/FleetX
공식 코드https://github.com/PaddlePaddle/Paddle
공식 코드https://github.com/Photon-AI-Research/NeuralSolvers
공식 코드Large-scale Neural Solvers for Partial Differential Equations
https://github.com/RixonC/DINGO
공식 코드DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization
https://github.com/SciEcon/IncidentsAnalysis2023
공식 코드https://github.com/Tencent/TFace
공식 코드https://github.com/WesleyZhang1991/GCN_rerank
공식 코드Graph Convolution Based Efficient Re-Ranking for Visual Retrieval
https://github.com/XiaoFuLab/federated_max_var_gcca
공식 코드Communication-Efficient Federated Linear and Deep Generalized Canonical Correlation Analysis
https://github.com/ZW-ZHANG/RandNE
공식 코드Billion-scale Network Embedding with Iterative Random Projection
https://github.com/Zhong-Zhengyi/SacFL-Code
공식 코드SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices
https://github.com/aamirshafi/distributed
공식 코드Efficient MPI-based Communication for GPU-Accelerated Dask Applications
https://github.com/aaron-wheeler/brokerage.jl
공식 코드Scalable Agent-Based Modeling for Complex Financial Market Simulations
https://github.com/aaron-wheeler/tradingagents.jl
공식 코드Scalable Agent-Based Modeling for Complex Financial Market Simulations
https://github.com/aiming-lab/CITER
공식 코드CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level Routing
https://github.com/alaaselim-sudo/-rllib-impala
공식 코드Scalable Volt-VAR Optimization using RLlib-IMPALA Framework: A Reinforcement Learning Approach
https://github.com/alberta-lee/nc-24
공식 코드Online Parallel Multi-Task Relationship Learning via Alternating Direction Method of Multipliers
https://github.com/alibaba/data-juicer
공식 코드Data-Juicer: A One-Stop Data Processing System for Large Language Models
https://github.com/anpar/EE-WCC-MapReduce
공식 코드Energy-Efficient Edge-Facilitated Wireless Collaborative Computing using Map-Reduce
https://github.com/azalia/RankMap
공식 코드RankMap: A Platform-Aware Framework for Distributed Learning from Dense Datasets
https://github.com/baoqianwang/iros22_darl1n
공식 코드https://github.com/bingyuan-zhang/tgcc
공식 코드https://github.com/bingyuan-zhang/tgcc_simulation_code
공식 코드https://github.com/blayes/adda
공식 코드Asynchronous and Distributed Data Augmentation for Massive Data Settings
https://github.com/chaoyanghe/Awesome-Federated-Learning
공식 코드FedML: A Research Library and Benchmark for Federated Machine Learning
https://github.com/chuangtaochen-tum/livemind
공식 코드LiveMind: Low-latency Large Language Models with Simultaneous Inference
https://github.com/danmackinlay/genbp
공식 코드Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.