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Distributed Computing

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/davidwarne/Bayesian_SIMD_examples

공식 코드

Vector operations for accelerating expensive Bayesian computations -- a tutorial guide

https://github.com/dengnianchen/fovnerf

공식 코드

FoV-NeRF: Foveated Neural Radiance Fields for Virtual Reality

https://github.com/dobriban/dist_ridge

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WONDER: Weighted one-shot distributed ridge regression in high dimensions

https://github.com/evolutionary-intelligence/dcc

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Cooperative Coevolution for Non-Separable Large-Scale Black-Box Optimization: Convergence Analyses and Distributed Accelerations

https://github.com/fredericometelo/peersim-environment

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PeersimGym: An Environment for Solving the Task Offloading Problem with Reinforcement Learning

https://github.com/fredericometelo/taskoffloadingagentlibrary

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PeersimGym: An Environment for Solving the Task Offloading Problem with Reinforcement Learning

https://github.com/google-research/google-research

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Scalable Differentially Private Clustering via Hierarchically Separated Trees

https://github.com/gradiustwinbee/glis

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Global-Local Collaborative Inference with LLM for Lidar-Based Open-Vocabulary Detection

https://github.com/hpcaitech/skycomputing

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Sky Computing: Accelerating Geo-distributed Computing in Federated Learning

https://github.com/hubdaniel/satellite-imagery-driven-geospatial-intelligence-system-for-tracking-economic-dynamics

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CrossVIT-augmented Geospatial-Intelligence Visualization System for Tracking Economic Development Dynamics

https://github.com/hwangdongjun/federated_learning_using_websockets

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Improving Response Time of Home IoT Services in Federated Learning

https://github.com/iil-postech/semantic-attention

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Attention-aware Semantic Communications for Collaborative Inference

https://github.com/imperial-qore/COSCO

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MCDS: AI Augmented Workflow Scheduling in Mobile Edge Cloud Computing Systems

https://github.com/intel-analytics/BigDL

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BigDL 2.0: Seamless Scaling of AI Pipelines from Laptops to Distributed Cluster

https://github.com/ipc-lab/collaborative-inference-oac

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Private Collaborative Edge Inference via Over-the-Air Computation

https://github.com/kunglab/ddnn

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Distributed Deep Neural Networks over the Cloud, the Edge and End Devices

https://github.com/lanl/t-elf

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Binary Bleed: Fast Distributed and Parallel Method for Automatic Model Selection

https://github.com/learning-at-home/hivemind

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Petals: Collaborative Inference and Fine-tuning of Large Models

https://github.com/liamcli/darts_asha

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A System for Massively Parallel Hyperparameter Tuning

https://github.com/lirongx/SubNN

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Achieving the time of $1$-NN, but the accuracy of $k$-NN

https://github.com/lx10077/LocalPower

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Communication-Efficient Distributed SVD via Local Power Iterations

https://github.com/maymalka10/ensembles-on-the-edge

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Decentralized Low-Latency Collaborative Inference via Ensembles on the Edge

https://github.com/moe-inf/awesome-moe-inference

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A Survey on Inference Optimization Techniques for Mixture of Experts Models

https://github.com/nasiryahm/correlationsruingd

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Correlations Are Ruining Your Gradient Descent

https://github.com/pasta41/lml-2020

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Accuracy-Efficiency Trade-Offs and Accountability in Distributed ML Systems

https://github.com/pfnet/optuna

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Optuna: A Next-generation Hyperparameter Optimization Framework

https://github.com/purbeshmitra/distributed_moa

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Distributed Mixture-of-Agents for Edge Inference with Large Language Models

https://github.com/qiongwu86/v2x-assisted-distributed-computing-and-control-framework-for-connected-and-automated-vehicles

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V2X-Assisted Distributed Computing and Control Framework for Connected and Automated Vehicles under Ramp Merging Scenario

https://github.com/rezafuru/quantensplit

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Architectural Vision for Quantum Computing in the Edge-Cloud Continuum

https://github.com/ryadzenine/dolphin

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Online Asynchronous Distributed Regression

https://github.com/sahelyiyi/FederatedLearning

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Clustered Federated Learning via Generalized Total Variation Minimization

https://github.com/sharc-lab/residual-inr

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Residual-INR: Communication Efficient On-Device Learning Using Implicit Neural Representation

https://github.com/shenqianli/fg2u

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Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization

https://github.com/sjtu-marl/malib

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MALib: A Parallel Framework for Population-based Multi-agent Reinforcement Learning

https://github.com/software-engineering-amsterdam/MLitB

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MLitB: Machine Learning in the Browser

https://github.com/solidlabnetwork/awesome-distributed-LLM

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Distributed LLMs and Multimodal Large Language Models: A Survey on Advances, Challenges, and Future Directions

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.