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Project or Job Scheduling
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hfl15/windpred
공식 코드A Spatiotemporal Deep Neural Network for Fine-Grained Multi-Horizon Wind Prediction
https://github.com/hgl71964/cuasmrl
공식 코드CuAsmRL: Optimizing GPU SASS Schedules via Deep Reinforcement Learning
https://github.com/hidet-org/hidet
공식 코드Hidet: Task-Mapping Programming Paradigm for Deep Learning Tensor Programs
https://github.com/hlzhang109/critical-batch-size
공식 코드https://github.com/hmxiong/streamchat
공식 코드Streaming Video Understanding and Multi-round Interaction with Memory-enhanced Knowledge
https://github.com/homaei/digitaltwin-water-ml
공식 코드Digital Transformation in the Water Distribution System based on the Digital Twins Concept
https://github.com/hongzimao/decima-sim
공식 코드https://github.com/hpaulkeeler/detcov
공식 코드Coverage probability in wireless networks with determinantal scheduling
https://github.com/hpaulkeeler/detcov_matlab
공식 코드Coverage probability in wireless networks with determinantal scheduling
https://github.com/hpcaitech/colossalai
공식 코드https://github.com/hpcclab/Felare
공식 코드FELARE: Fair Scheduling of Machine Learning Tasks on Heterogeneous Edge Systems
https://github.com/hplt-project/opuscleaner
공식 코드https://github.com/hplt-project/opustrainer
공식 코드https://github.com/hu-po/pySACQ
공식 코드Learning by Playing - Solving Sparse Reward Tasks from Scratch
https://github.com/huawei-noah/hebo
공식 코드https://github.com/hugorichard/ml4a-scheduling
공식 코드https://github.com/hupihe/rsd4
공식 코드Effective Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning
https://github.com/huttered40/cpr-perf-model
공식 코드https://github.com/ibm/assetopsbench
공식 코드https://github.com/icidsl/harflow3d
공식 코드HARFLOW3D: A Latency-Oriented 3D-CNN Accelerator Toolflow for HAR on FPGA Devices
https://github.com/icloud-ecnu/opara
공식 코드Opara: Exploiting Operator Parallelism for Expediting DNN Inference on GPUs
https://github.com/icon-lab/SelfRDB
공식 코드Self-Consistent Recursive Diffusion Bridge for Medical Image Translation
https://github.com/ict-net/NetGPT
공식 코드NetGPT: Generative Pretrained Transformer for Network Traffic
https://github.com/iiduka-researches/igo-aaai25
공식 코드Explicit and Implicit Graduated Optimization in Deep Neural Networks
https://github.com/imperial-qore/COSCO
공식 코드HUNTER: AI based Holistic Resource Management for Sustainable Cloud Computing
https://github.com/imperial-qore/metanet
공식 코드MetaNet: Automated Dynamic Selection of Scheduling Policies in Cloud Environments
https://github.com/ingambe/End2End-Job-Shop-Scheduling-CP
공식 코드https://github.com/ingambe/rl4semiconductorfabsched
공식 코드Semiconductor Fab Scheduling with Self-Supervised and Reinforcement Learning
https://github.com/instadeepai/compass
공식 코드Combinatorial Optimization with Policy Adaptation using Latent Space Search
https://github.com/internlandmark/flashgs
공식 코드FlashGS: Efficient 3D Gaussian Splatting for Large-scale and High-resolution Rendering
https://github.com/internlm/acmetrace
공식 코드Characterization of Large Language Model Development in the Datacenter
https://github.com/irfansha/q-synth
공식 코드Optimal Layout Synthesis for Deep Quantum Circuits on NISQ Processors with 100+ Qubits
https://github.com/ismetdagli/hax-conn
공식 코드Shared Memory-contention-aware Concurrent DNN Execution for Diversely Heterogeneous System-on-Chips
https://github.com/ist-daslab/marlin
공식 코드MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models
https://github.com/ist-daslab/sparse-marlin
공식 코드MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.