high performance computing on graphics processing units: hgpu.org

hgpu.org » Task scheduling

Task scheduling in hybrid CPU-GPU systems

Martin Krulis, Zbynek Falt, David Bednarek, Jakub Yaghob

View

Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, OpenCL, Operating systems, Task scheduling, Tesla M2090

June 2, 2013 by hgpu

An Automatic Input-Sensitive Approach for Heterogeneous Task Partitioning

Klaus Kofler, Ivan Grasso, Biagio Cosenza, Thomas Fahringer

View

Download (PDF)

Tags: ATI, ATI Radeon HD 5870, Code generation, Compilers, Computer science, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Task scheduling

April 21, 2013 by hgpu

LU Factorization with Partial Pivoting for a Multi-CPU, Multi-GPU Shared Memory System

Jakub Kurzak, P. Luszczek, Mathieu Faverge, Jack J. Dongarra

View

Download (PDF)

Tags: Computer science, CUDA, Factorization, nVidia, Task scheduling, Tesla S2050

April 17, 2013 by hgpu

Load Balancing in a Changing World: Dealing with Heterogeneity and Performance Variability

Michael Boyer, Kevin Skadron, Shuai Che, Nuwan Jayasena

View

Download (PDF)

Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 6670, Computer science, Heterogeneous systems, OpenCL, Performance, Task scheduling

April 8, 2013 by hgpu

Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling

Jianlong Zhong, Bingsheng He

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, PTX, Task scheduling, Tesla C2050

March 23, 2013 by hgpu

Using Graphical Processing Units for Deterministic Single Machine Scheduling Problems

Krisztian Mihaly, Oliver Hornyak

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 520 M, Task scheduling

March 7, 2013 by hgpu

Scheduling a Parallel Sparse Direct Solver to Multiple GPUs

Kyungjoo Kim

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Factorization, FEM, Finite element method, Heterogeneous systems, nVidia, Package, Sparse direct solvers, Task scheduling, Tesla M2070

February 21, 2013 by hgpu

Efficient Exploitation of Heterogeneous Platforms for Vertebra Detection in X-Ray Images

Sidi Ahmed Mahmoudi, Fabian Lecron, Pierre Manneback, Mohammed Benjelloun and Said Mahmoudi

View

Download (PDF)

Tags: CUDA, Heterogeneous systems, Image processing, nVidia, Task scheduling

February 1, 2013 by hgpu

Scheduling (ir)regular applications on heterogeneous platforms

Artur Miguel Matos Mariano

View

Download (PDF)

Tags: Computer science, CUDA, FFT, Heterogeneous systems, N-body simulation, nVidia, nVidia GeForce GTX 580, Task scheduling, Thesis

January 30, 2013 by hgpu

Efficient Implementation of MrBayes on multi-GPU

Jie Bao, Hongju Xia, Jianfu Zhou, Xiaoguang Liu, Gang Wang

View

Download (PDF)

Source codes

Tags: Bayesian, Biology, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 480, Package, Task scheduling

January 28, 2013 by hgpu

Softshell: Dynamic Scheduling on GPUs

Markus Steinberger, Bernhard Kainz, Bernhard Kerbl, Stefan Hauswiesner, Michael Kenzel, Dieter Schmalstieg

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Quadro FX 6000, Package, Task scheduling

November 27, 2012 by hgpu

The Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System

Qingyu Meng, Alan Humphrey, Martin Berzins

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, Memory model, MPI, nVidia, nVidia GeForce GTX 570, Task scheduling, Tesla C2070

November 24, 2012 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Task scheduling in hybrid CPU-GPU systems

An Automatic Input-Sensitive Approach for Heterogeneous Task Partitioning

LU Factorization with Partial Pivoting for a Multi-CPU, Multi-GPU Shared Memory System

Load Balancing in a Changing World: Dealing with Heterogeneity and Performance Variability

Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling

Using Graphical Processing Units for Deterministic Single Machine Scheduling Problems

Scheduling a Parallel Sparse Direct Solver to Multiple GPUs

Efficient Exploitation of Heterogeneous Platforms for Vertebra Detection in X-Ray Images

Scheduling (ir)regular applications on heterogeneous platforms

Efficient Implementation of MrBayes on multi-GPU

Softshell: Dynamic Scheduling on GPUs

The Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Most viewed papers (last 30 days)