netx-repo / PipeSwitchLinks
PipeSwitch: Fast Pipelined Context Switching for Deep Learning Applications
☆126Updated 3 years ago
Alternatives and similar repositories for PipeSwitch
Users that are interested in PipeSwitch are comparing it to the libraries listed below
Sorting:
- Fine-grained GPU sharing primitives☆147Updated 4 months ago
- Model-less Inference Serving☆91Updated 2 years ago
- ☆38Updated 5 months ago
- ☆82Updated 5 months ago
- ☆51Updated 2 years ago
- Tiresias is a GPU cluster manager for distributed deep learning training.☆164Updated 5 years ago
- ☆53Updated 11 months ago
- Code for "Heterogenity-Aware Cluster Scheduling Policies for Deep Learning Workloads", which appeared at OSDI 2020☆133Updated last year
- A GPU-accelerated DNN inference serving system that supports instant kernel preemption and biased concurrent execution in GPU scheduling.☆43Updated 3 years ago
- DISB is a new DNN inference serving benchmark with diverse workloads and models, as well as real-world traces.☆57Updated last year
- AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving (OSDI 23)☆91Updated 2 years ago
- Bamboo is a system for running large pipeline-parallel DNNs affordably, reliably, and efficiently using spot instances.☆54Updated 2 years ago
- Artifacts for our ASPLOS'23 paper ElasticFlow☆55Updated last year
- REEF is a GPU-accelerated DNN inference serving system that enables instant kernel preemption and biased concurrent execution in GPU sche…☆103Updated 2 years ago
- Helios Traces from SenseTime☆62Updated 3 years ago
- ☆198Updated 6 years ago
- GPU-scheduler-for-deep-learning☆210Updated 5 years ago
- Analyze network performance in distributed training☆19Updated 5 years ago
- Artifact of OSDI '24 paper, ”Llumnix: Dynamic Scheduling for Large Language Model Serving“☆63Updated last year
- Artifact for "Shockwave: Fair and Efficient Cluster Scheduling for Dynamic Adaptation in Machine Learning" [NSDI '23]☆46Updated 3 years ago
- ☆57Updated 4 years ago
- Artifacts for our SIGCOMM'22 paper Muri☆44Updated last year
- ☆38Updated 4 years ago
- An Efficient Pipelined Data Parallel Approach for Training Large Model☆76Updated 4 years ago
- Paella: Low-latency Model Serving with Virtualized GPU Scheduling☆65Updated last year
- Artifacts for our NSDI'23 paper TGS☆90Updated last year
- BytePS examples (Vision, NLP, GAN, etc)☆19Updated 3 years ago
- SOTA Learning-augmented Systems☆37Updated 3 years ago
- An experimental parallel training platform☆56Updated last year
- An Efficient Dynamic Resource Scheduler for Deep Learning Clusters☆41Updated 8 years ago