ParCIS / Ok-TopkLinks
Ok-Topk is a scheme for distributed training with sparse gradients. Ok-Topk integrates a novel sparse allreduce algorithm (less than 6k communication volume which is asymptotically optimal) with the decentralized parallel Stochastic Gradient Descent (SGD) optimizer, and its convergence is proved theoretically and empirically.
☆26Updated 2 years ago
Alternatives and similar repositories for Ok-Topk
Users that are interested in Ok-Topk are comparing it to the libraries listed below
Sorting:
- Hi-Speed DNN Training with Espresso: Unleashing the Full Potential of Gradient Compression with Near-Optimal Usage Strategies (EuroSys '2…☆15Updated last year
- A Cluster-Wide Model Manager to Accelerate DNN Training via Automated Training Warmup☆35Updated 2 years ago
- ☆14Updated 3 years ago
- ☆20Updated 3 years ago
- Cupcake: A Compression Scheduler for Scalable Communication-Efficient Distributed Training (MLSys '23)☆9Updated 2 years ago
- SHADE: Enable Fundamental Cacheability for Distributed Deep Learning Training☆35Updated 2 years ago
- Artifact for PPoPP22 QGTC: Accelerating Quantized GNN via GPU Tensor Core.☆30Updated 3 years ago
- ☆10Updated 2 years ago
- Artifact for OSDI'23: MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Mult…☆40Updated last year
- ☆24Updated 2 years ago
- ☆25Updated last year
- Artifacts for our SIGCOMM'22 paper Muri☆41Updated last year
- Open-source implementation for "Helix: Serving Large Language Models over Heterogeneous GPUs and Network via Max-Flow"☆59Updated 8 months ago
- ☆37Updated last month
- DISB is a new DNN inference serving benchmark with diverse workloads and models, as well as real-world traces.☆53Updated 11 months ago
- [ACM EuroSys 2023] Fast and Efficient Model Serving Using Multi-GPUs with Direct-Host-Access☆57Updated this week
- Compiler for Dynamic Neural Networks☆46Updated last year
- Artifacts for our ASPLOS'23 paper ElasticFlow☆52Updated last year
- ☆38Updated last year
- ☆30Updated last year
- ☆51Updated 2 years ago
- Artifact for OSDI'21 GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs.☆66Updated 2 years ago
- LLM serving cluster simulator☆108Updated last year
- A GPU-accelerated DNN inference serving system that supports instant kernel preemption and biased concurrent execution in GPU scheduling.☆42Updated 3 years ago
- [ASPLOS'23] Optimus-CC: Efficient Large NLP Model Training with 3D Parallelism Aware Communication Compression☆6Updated 11 months ago
- Tacker: Tensor-CUDA Core Kernel Fusion for Improving the GPU Utilization while Ensuring QoS☆31Updated 5 months ago
- SOTA Learning-augmented Systems☆36Updated 3 years ago
- ☆39Updated 2 years ago
- AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving (OSDI 23)☆83Updated 2 years ago
- ☆16Updated 2 years ago