ruipeterpan / cs759-sp21
CS/ECE/ME/EP 759 (High Performance Computing for Engineering Applications) Course Project: Cautiously Aggressive GPU Space Sharing to Improve Resource Utilization and Job Efficiency
☆8Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for cs759-sp21
- Code for "Shockwave: Fair and Efficient Cluster Scheduling for Dynamic Adaptation in Machine Learning" [NSDI '23]☆38Updated last year
- ☆23Updated last year
- Artifacts for our ASPLOS'23 paper ElasticFlow☆52Updated 6 months ago
- Bamboo is a system for running large pipeline-parallel DNNs affordably, reliably, and efficiently using spot instances.☆47Updated last year
- Personal blog + reading notes on system-ish papers☆15Updated last year
- SOTA Learning-augmented Systems☆33Updated 2 years ago
- ☆51Updated 3 years ago
- ☆23Updated 2 years ago
- A GPU-accelerated DNN inference serving system that supports instant kernel preemption and biased concurrent execution in GPU scheduling.☆39Updated 2 years ago
- ☆73Updated last year
- ☆37Updated 3 years ago
- My paper/code reading notes in Chinese☆45Updated 6 months ago
- ☆31Updated 5 months ago
- DISB is a new DNN inference serving benchmark with diverse workloads and models, as well as real-world traces.☆54Updated 3 months ago
- Thinking is hard - automate it☆18Updated 2 years ago
- A Cluster-Wide Model Manager to Accelerate DNN Training via Automated Training Warmup☆34Updated last year
- Adaptive Message Quantization and Parallelization for Distributed Full-graph GNN Training☆20Updated 8 months ago
- website for systems seminar at UIUC☆17Updated this week
- REEF is a GPU-accelerated DNN inference serving system that enables instant kernel preemption and biased concurrent execution in GPU sche…☆85Updated last year
- Code for "Apparate: Rethinking Early Exits to Tame Latency-Throughput Tensions in ML Serving" [SOSP '24]☆16Updated this week
- ☆13Updated 2 years ago
- Dorylus: Affordable, Scalable, and Accurate GNN Training☆77Updated 3 years ago
- ☆16Updated last year
- Stateful LLM Serving☆38Updated 3 months ago
- Analyze network performance in distributed training☆16Updated 4 years ago
- Artifacts for our SIGCOMM'22 paper Muri☆40Updated 10 months ago
- An experimental parallel training platform☆52Updated 7 months ago
- Boost hardware utilization for ML training workloads via Inter-model Horizontal Fusion☆32Updated 6 months ago
- ☆21Updated 6 years ago
- FGNN's artifact evaluation (EuroSys 2022)☆17Updated 2 years ago