lzhangbv / acpsgd
[ICDCS 2023] Evaluation and Optimization of Gradient Compression for Distributed Deep Learning
☆10Updated last year
Alternatives and similar repositories for acpsgd:
Users that are interested in acpsgd are comparing it to the libraries listed below
- AN EFFICIENT AND GENERAL FRAMEWORK FOR LAYERWISE-ADAPTIVE GRADIENT COMPRESSION☆13Updated last year
- ☆49Updated last year
- Ok-Topk is a scheme for distributed training with sparse gradients. Ok-Topk integrates a novel sparse allreduce algorithm (less than 6k c…☆24Updated 2 years ago
- Code associated with the paper **Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees**.☆27Updated last year
- CoreScheduler: A High-Performance Scheduler for Large Model Training☆21Updated 5 months ago
- ☆9Updated last year
- Create tiny ML systems for on-device learning.☆20Updated 3 years ago
- A Cluster-Wide Model Manager to Accelerate DNN Training via Automated Training Warmup☆34Updated 2 years ago
- Pytorch implementation of our paper accepted by ICML 2024 -- CaM: Cache Merging for Memory-efficient LLMs Inference☆32Updated 7 months ago
- Efficient LLM Inference Acceleration using Prompting☆46Updated 3 months ago
- PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models. ICML 2021☆55Updated 3 years ago
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆46Updated last year
- ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction (NIPS'24)☆26Updated last month
- Official resporitory for "IPDPS' 24 QSync: Quantization-Minimized Synchronous Distributed Training Across Hybrid Devices".☆19Updated 11 months ago
- SQUEEZED ATTENTION: Accelerating Long Prompt LLM Inference☆40Updated 2 months ago
- ☆23Updated 3 months ago
- ☆14Updated 3 years ago
- [ICDCS 2023] DeAR: Accelerating Distributed Deep Learning with Fine-Grained All-Reduce Pipelining☆12Updated last year
- (NeurIPS 2022) Automatically finding good model-parallel strategies, especially for complex models and clusters.☆37Updated 2 years ago
- ☆19Updated last year
- ☆12Updated 2 years ago
- [ICML 2024] Serving LLMs on heterogeneous decentralized clusters.☆19Updated 9 months ago
- Official implementation for Yuan & Liu & Zhong et al., KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark o…☆63Updated last month
- Open-source implementation for "Helix: Serving Large Language Models over Heterogeneous GPUs and Network via Max-Flow"☆18Updated 2 months ago
- The implementation for MLSys 2023 paper: "Cuttlefish: Low-rank Model Training without All The Tuning"☆43Updated last year
- ☆41Updated 2 years ago
- ☆14Updated 3 years ago
- ☆20Updated last year
- [ICLR 2025] TidalDecode: A Fast and Accurate LLM Decoding with Position Persistent Sparse Attention☆26Updated this week
- Code for reproducing experiments performed for Accoridon☆13Updated 3 years ago