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SUPERGLUE: A Shared Memory Framework Using Data Versioning for Dependency-Aware Task-Based Parallelization

Martin Tillenius

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenMP, Package, Task scheduling

April 29, 2014 by hgpu

Heterogeneous Computing and Grid Scheduling with Hierarchically Parallel Evolutionary Algorithms

Jinglian Wang, Bin Gong, Hong Liu, Shaohui Li, Juan Yi

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Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, Task scheduling

April 29, 2014 by hgpu

A GPU-Based Enhanced Genetic Algorithm for Power-Aware Task Scheduling Problem in HPC Cloud

Nguyen Quang-Hung, Le Thanh Tan, Chiem Thach Phat, Nam Thoai

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Tags: Cloud, Computer science, CUDA, nVidia, Probability, Task scheduling, Tesla M2090

April 21, 2014 by hgpu

Scheduling Dataflow Execution Across Multiple Accelerators

Jon Currey, Adam Eversole, Christopher J. Rossbach

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Tags: Computer science, CUDA, nVidia, Task scheduling, Tesla K20

April 14, 2014 by hgpu

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Luka Stanisic, Samuel Thibault, Arnaud Legrand, Brice Videau, Jean-Francois Mehaut

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Performance, Task scheduling, Tesla C2050, Tesla K20, Tesla M2075

April 9, 2014 by hgpu

A two-level task scheduler on Multiple DSP system for OpenCL

Li Tian, Cai Meng, Fugen Zhou

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Tags: Computer science, DSP, nVidia, OpenCL, Task scheduling

April 9, 2014 by hgpu

Dynamic Load Balancing using Graphics Processors

R. Mohan, N. P. Gopalan

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

March 18, 2014 by hgpu

GPU-EvR: Run-time Event Based Real-time Scheduling Framework on GPGPU Platform

Haeseung Lee, Mohammad Abdullah Al Faruque

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Tags: Computer science, nVidia, Task scheduling, Tesla K20

March 10, 2014 by hgpu

Converting Data to Task-Parallelism by Rewrites

Ryan R. Newton, Eric Holk, Trevor L. McDonell

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Tags: Computer science, CUDA, Haskell, nVidia, Package, Task scheduling, Tesla C2075

March 7, 2014 by hgpu

Extending a Run-time Resource Management framework to support OpenCL and Heterogeneous Systems

Giuseppe Massari, Chiara Caffarri, Patrick Bellasi, William Fornaciari

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Tags: ATI, ATI Radeon HD 7750, Computer science, OpenCL, Task scheduling

February 28, 2014 by jumanix

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, Matrix multiplication, Memory model, nVidia, Prefetch, Task scheduling, Tesla M2070

February 11, 2014 by hgpu

Consolidating Applications for Energy Efficiency in Heterogeneous Computing Systems

Jing Zhang, Hao Wang, Heshan Lin, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL, Task scheduling

January 29, 2014 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

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high performance computing on graphics processing units: hgpu.org

SUPERGLUE: A Shared Memory Framework Using Data Versioning for Dependency-Aware Task-Based Parallelization

Heterogeneous Computing and Grid Scheduling with Hierarchically Parallel Evolutionary Algorithms

Scheduling Dataflow Execution Across Multiple Accelerators

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

A two-level task scheduler on Multiple DSP system for OpenCL

Dynamic Load Balancing using Graphics Processors

GPU-EvR: Run-time Event Based Real-time Scheduling Framework on GPGPU Platform

Converting Data to Task-Parallelism by Rewrites

Extending a Run-time Resource Management framework to support OpenCL and Heterogeneous Systems

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Consolidating Applications for Energy Efficiency in Heterogeneous Computing Systems

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

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