hku-systems / naspipeLinks
☆14Updated 3 years ago
Alternatives and similar repositories for naspipe
Users that are interested in naspipe are comparing it to the libraries listed below
Sorting:
- ☆25Updated 2 years ago
- ☆21Updated 3 years ago
- DISB is a new DNN inference serving benchmark with diverse workloads and models, as well as real-world traces.☆54Updated 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…☆27Updated 2 years ago
- A Cluster-Wide Model Manager to Accelerate DNN Training via Automated Training Warmup☆35Updated 2 years ago
- Artifact for "Apparate: Rethinking Early Exits to Tame Latency-Throughput Tensions in ML Serving" [SOSP '24]☆25Updated 11 months ago
- ☆28Updated last month
- ☆10Updated 2 years ago
- ☆14Updated last week
- Boost hardware utilization for ML training workloads via Inter-model Horizontal Fusion☆32Updated last year
- Supplemental materials for The ASPLOS 2025 / EuroSys 2025 Contest on Intra-Operator Parallelism for Distributed Deep Learning☆23Updated 6 months ago
- ☆38Updated 4 months ago
- Artifact for OSDI'23: MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Mult…☆40Updated last year
- ☆24Updated 3 years ago
- Tacker: Tensor-CUDA Core Kernel Fusion for Improving the GPU Utilization while Ensuring QoS☆32Updated 9 months ago
- ☆15Updated 3 years ago
- An Attention Superoptimizer☆22Updated 9 months ago
- Cavs: An Efficient Runtime System for Dynamic Neural Networks☆15Updated 5 years ago
- Compiler for Dynamic Neural Networks☆46Updated 2 years ago
- MAGIS: Memory Optimization via Coordinated Graph Transformation and Scheduling for DNN (ASPLOS'24)☆55Updated last year
- SOTA Learning-augmented Systems☆37Updated 3 years ago
- A GPU-accelerated DNN inference serving system that supports instant kernel preemption and biased concurrent execution in GPU scheduling.☆43Updated 3 years ago
- AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving (OSDI 23)☆91Updated 2 years ago
- ☆57Updated 4 years ago
- FGNN's artifact evaluation (EuroSys 2022)☆17Updated 3 years ago
- Source code for the paper: "A Latency-Predictable Multi-Dimensional Optimization Framework forDNN-driven Autonomous Systems"☆22Updated 4 years ago
- Artifacts for our ASPLOS'23 paper ElasticFlow☆55Updated last year
- Proteus: A High-Throughput Inference-Serving System with Accuracy Scaling☆13Updated last year
- ☆31Updated 4 months ago
- ☆17Updated 2 years ago