romilbhardwaj / kube-tutorialLinks
Kubernetes Tutorial for the PS2 group meetings at UC Berkeley
☆15Updated 2 years ago
Alternatives and similar repositories for kube-tutorial
Users that are interested in kube-tutorial are comparing it to the libraries listed below
Sorting:
- Bamboo is a system for running large pipeline-parallel DNNs affordably, reliably, and efficiently using spot instances.☆50Updated 2 years ago
- ☆53Updated 4 years ago
- ☆44Updated 3 years ago
- ☆24Updated last year
- ☆14Updated 3 years ago
- A universal workflow system for exactly-once DAGs☆23Updated 2 years ago
- A resilient distributed training framework☆95Updated last year
- ML Input Data Processing as a Service. This repository contains the source code for Cachew (built on top of TensorFlow).☆38Updated 8 months ago
- Random collections of my interested research papers / projects☆20Updated 4 years ago
- Dorylus: Affordable, Scalable, and Accurate GNN Training☆76Updated 4 years ago
- Repository for MLCommons Chakra schema and tools☆39Updated last year
- ☆36Updated 4 years ago
- The NYU Systems Seminar☆23Updated last year
- ☆15Updated 2 years ago
- My paper/code reading notes in Chinese☆46Updated last year
- ☆16Updated 2 years ago
- Artifact for "Apparate: Rethinking Early Exits to Tame Latency-Throughput Tensions in ML Serving" [SOSP '24]☆24Updated 6 months ago
- AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving (OSDI 23)☆81Updated last year
- Ultra | Ultimate | Unified CCL☆102Updated this week
- A GPU-accelerated DNN inference serving system that supports instant kernel preemption and biased concurrent execution in GPU scheduling.☆42Updated 3 years ago
- EuroSys '24: "Trinity: A Fast Compressed Multi-attribute Data Store"☆18Updated 2 months ago
- SHADE: Enable Fundamental Cacheability for Distributed Deep Learning Training☆34Updated 2 years ago
- DISB is a new DNN inference serving benchmark with diverse workloads and models, as well as real-world traces.☆52Updated 9 months ago
- (NeurIPS 2022) Automatically finding good model-parallel strategies, especially for complex models and clusters.☆38Updated 2 years ago
- ☆30Updated 2 years ago
- Selected Topics in Computer Networks @ Johns Hopkins University☆19Updated 4 years ago
- ☆79Updated 2 years ago
- An Attention Superoptimizer☆21Updated 4 months ago
- Boost hardware utilization for ML training workloads via Inter-model Horizontal Fusion☆32Updated last year
- Microsoft Collective Communication Library☆65Updated 6 months ago