high performance computing on graphics processing units: hgpu.org

hgpu.org » Task scheduling

Enabling task-level scheduling on heterogeneous platforms

Enqiang Sun, Dana Schaa, Richard Bagley, Norman Rubin, David Kaeli

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Tags: ATI, ATI FirePro V9800, ATI Radeon HD 6970, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, OpenCL, Task scheduling

May 9, 2012 by hgpu

Heterogeneous Task Scheduling for Accelerated OpenMP

Thomas R. W. Scogland, Barry Rountree, Wu-chun Feng, Bronis R. de Supinski

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenMP, Task scheduling, Tesla C2050

May 4, 2012 by hgpu

Automatic NUMA Characterization using Cbench

Ryan Braithwaite, Wu-chun Feng, Patrick McCormick

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Package, Task scheduling, Tesla C2050

May 2, 2012 by hgpu

A Programmable Processing Array Architecture Supporting Dynamic Task Scheduling and Module-Level Prefetching

Junghee Lee, Hyung Gyu Lee, Soonhoi Ha, Jongman Kim, Chrysostomos Nicopoulos

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Quadro NVS 295, Prefetch, Programming techniques, Task scheduling

April 5, 2012 by hgpu

Scheduling Tasks over Multicore machines enhanced with Accelerators: a Runtime System’s Perspective

Cedric Augonnet

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Tags: Cell processor, Computer science, CUDA, Databases, nVidia, nVidia Quadro FX 4600, nVidia Quadro FX 5800, Task scheduling, Tesla C2050, Tesla M2070, Tesla S1070, Thesis

March 29, 2012 by hgpu

Globally scheduled real-time multiprocessor systems with GPUs

Glenn A. Elliott, James H. Anderson

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Task scheduling

March 16, 2012 by hgpu

Dynamic Task-Scheduling and Resource Management for GPU Accelerators in Medical Imaging

Richard Membarth, Jan-Hugo Lupp, Frank Hannig, Jurgen Teich, Mario Korner, Wieland Eckert

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Tags: CUDA, Image processing, Medicine, nVidia, nVidia Quadro FX 1800, Task scheduling, Tesla C2050

March 8, 2012 by hgpu

Using Graphical Processing Units in Scheduling Problems

K. Mihaly, O. Hornyak

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Tags: Algorithms, Computer science, CUDA, nVidia, Task scheduling, Tesla C1060

February 13, 2012 by hgpu

Work Stealing Inside GPUs

Julio Toss

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 280, Task scheduling, Tesla C2050, Thesis

February 13, 2012 by hgpu

Realtime scheduling using GPUs – proof of feasibility

Peter Fodrek, Ludovit Farkas, Tomas Murgas

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Tags: Benchmarking, Computer science, nVidia, nVidia GeForce GT 310 M, OpenCL, Task scheduling

January 25, 2012 by hgpu

On the Correctness of the SIMT Execution Model of GPUs

Axel Habermaier, Alexander Knapp

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Tags: Computer science, CUDA, nVidia, Task scheduling, Thesis

January 20, 2012 by hgpu

Low-power Task Scheduling for GPU Energy Reduction

Li Tang, Yiji Zhang

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 210, nVidia GeForce GTX 280, nVidia GeForce GTX 570, Operating systems, Task scheduling

January 6, 2012 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

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high performance computing on graphics processing units: hgpu.org

Enabling task-level scheduling on heterogeneous platforms

Heterogeneous Task Scheduling for Accelerated OpenMP

Automatic NUMA Characterization using Cbench

A Programmable Processing Array Architecture Supporting Dynamic Task Scheduling and Module-Level Prefetching

Scheduling Tasks over Multicore machines enhanced with Accelerators: a Runtime System’s Perspective

Globally scheduled real-time multiprocessor systems with GPUs

Dynamic Task-Scheduling and Resource Management for GPU Accelerators in Medical Imaging

Using Graphical Processing Units in Scheduling Problems

Work Stealing Inside GPUs

Realtime scheduling using GPUs – proof of feasibility

On the Correctness of the SIMT Execution Model of GPUs

Low-power Task Scheduling for GPU Energy Reduction

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

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