high performance computing on graphics processing units: hgpu.org

hgpu.org » Task scheduling

Scheduling Languages: A Past, Present, and Future Taxonomy

Mary Hall, Cosmin Oancea, Anne C. Elster, Ari Rasch, Sameeran Joshi, Amir Mohammad Tavakkoli, Richard Schulze

View

Download (PDF)

Tags: Auto-Tuning, Compilers, Computer science, Performance, Programming Languages, Task scheduling

November 3, 2024 by hgpu

Is the GPU Half-Empty or Half-Full? Practical Scheduling Techniques for LLMs

Ferdi Kossmann, Bruce Fontaine, Daya Khudia, Michael Cafarella, Samuel Madden

View

Download (PDF)

Tags: Computer science, LLM, NLP, nVidia, nVidia A100, nVidia H100, Task scheduling

November 3, 2024 by hgpu

Efficient Configuration of Heterogeneous Resources and Task Scheduling Strategies in Deep Learning Auto-Tuning Systems

Pao-Yi Ken, Chao-Chin Wu

View

Download (PDF)

Tags: AI, Artificial intelligence, Computer science, Deep learning, Machine learning, nVidia, nVidia RTX A6000, Task scheduling

October 20, 2024 by hgpu

Scheduling Deep Learning Jobs in Multi-Tenant GPU Clusters via Wise Resource Sharing

Yizhou Luo, Qiang Wang, Shaohuai Shi, Jiaxin Lai, Shuhan Qi, Jiajia Zhang, Xuan Wang

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, GPU cluster, nVidia, nVidia GeForce RTX 2080 Ti, OpenMPI, PyTorch, Task scheduling

August 4, 2024 by hgpu

Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach

Urvij Saroliya, Eishi Arima, Dai Liu, Martin Schulz

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia A100, PC cluster, Task scheduling

May 20, 2024 by hgpu

Workload Scheduling on Heterogeneous Devices

Harsh Khetawat, Frank Mueller

View

Download (PDF)

Tags: Computer science, FPGA, Heterogeneous systems, nVidia, nVidia GeForce RTX 2060, OpenCL, Task scheduling

May 20, 2024 by hgpu

Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey

Feng Liang, Zhen Zhang, Haifeng Lu, Victor C. M. Leung, Yanyi Guo, Xiping Hu

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia A100, survey, Task scheduling

April 21, 2024 by hgpu

KeSCo: Compiler-based Kernel Scheduling for Multi-task GPU Applications

Zejia Lin, Zewei Mo, Xuanteng Huang, Xianwei Zhang, Yutong Lu

View

Download (PDF)

Tags: Benchmarking, Compilers, Computer science, CUDA, nVidia, nVidia A100, Task scheduling

December 24, 2023 by hgpu

FIKIT: Priority-Based Real-time GPU Multi-tasking Scheduling with Kernel Identification

Wenqing Wu

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce RTX 3090, nVidia GeForce RTX 4080 Ti, nVidia H100, Task scheduling

November 27, 2023 by hgpu

Compute units in OpenMP: Extensions for heterogeneous parallel programming

Marc Gonzàlez-Tallada, Enric Morancho

View

Download (PDF)

Tags: AMD Radeon Instinct Mi50, ATI, Benchmarking, Computer science, Heterogeneous systems, OpenMP, Task scheduling

August 28, 2023 by hgpu

Towards Intelligent Runtime Framework for Distributed Heterogeneous Systems

Polykarpos Thomadakis

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, Nuclear physics, nVidia, OpenCL, Physics, Task scheduling, Tesla V100, Thesis

July 16, 2023 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Scheduling Languages: A Past, Present, and Future Taxonomy

Is the GPU Half-Empty or Half-Full? Practical Scheduling Techniques for LLMs

Efficient Configuration of Heterogeneous Resources and Task Scheduling Strategies in Deep Learning Auto-Tuning Systems

Scheduling Deep Learning Jobs in Multi-Tenant GPU Clusters via Wise Resource Sharing

Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach

Workload Scheduling on Heterogeneous Devices

Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey

KeSCo: Compiler-based Kernel Scheduling for Multi-task GPU Applications

FIKIT: Priority-Based Real-time GPU Multi-tasking Scheduling with Kernel Identification

Compute units in OpenMP: Extensions for heterogeneous parallel programming

Towards Intelligent Runtime Framework for Distributed Heterogeneous Systems

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Most viewed papers (last 30 days)