high performance computing on graphics processing units: hgpu.org

hgpu.org » Optimization

Gyrokinetic Particle-in-Cell Optimization on Emerging Multi- and Manycore Platforms

Kamesh Madduri, Eun-Jin Im, Khaled Z. Ibrahim, Samuel Williams, Stephane Ethier, Leonid Oliker

Tags: CUDA, nVidia, Optimization, Particle-in-cell methods, Plasma physics, Tesla C2050

March 9, 2011 by hgpu

Speculative Execution on Multi-GPU Systems

Gregory Diamos, Sudhakar Yalamanchili

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce 9800 GX2, Optimization, Performance, Tesla S870

March 6, 2011 by hgpu

Task management for irregular-parallel workloads on the GPU

Stanley Tzeng, Anjul Patney, John D. Owens

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Optimization, Performance, Presentation, Task scheduling

March 6, 2011 by hgpu

Dynamic load balancing on single- and multi-GPU systems

Long Chen, Oreste Villa, Sriram Krishnamoorthy, Guang R. Gao

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Tags: Computer science, CUDA, nVidia, Optimization, Performance, Task scheduling, Tesla C1060

March 6, 2011 by hgpu

Formal Description and Optimization Based High – Performance Computing on CUDA

Bo Li, Huacheng Zhao, Jingjing Liang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8600 GT, Optimization, Programming techniques

March 4, 2011 by hgpu

Architecture-Aware Optimization Targeting Multithreaded Stream Computing

Byunghyun Jang, Synho Do, Homer Pien, David Kaeli

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Tags: ATI, ATI Radeon HD 3870, Brook, Computer science, Optimization, Programming techniques

March 4, 2011 by hgpu

Automatic data movement and computation mapping for multi-level parallel architectures with explicitly managed memories

Muthu Manikandan Baskaran, Uday Bondhugula, Sriram Krishnamoorthy, J. Ramanujam, Atanas Rountev, P. Sadayappan

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Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Performance

February 28, 2011 by hgpu

A Tuning Framework for Software-Managed Memory Hierarchies

Manman Ren, Ji Young Park, Mike Houston, Alex Aiken, William J. Dally

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Tags: Algorithms, Cell processor, Compilers, Computer science, Optimization, Performance, Playstation, Programming Languages

February 26, 2011 by hgpu

Achieving a single compute device image in OpenCL for multiple GPUs

Jungwon Kim, Honggyu Kim, Joo H. Lee, Jaejin Lee

Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, OpenCL, Optimization

February 25, 2011 by hgpu

Data parallel loop statement extension to CUDA: GpuC

Zeki Bozkus, Rajeev Thakur, William Gropp, Ewing Lusk

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, OpenMP, Optimization

February 21, 2011 by hgpu

Program Optimization Study on a 128-Core GPU

Shane Ryoo, Christopher I. Rodrigues, Sam S. Stone, Sara S. Baghsorkhi, Sain-Zee Ueng, and Wen-mei W. Hwu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Programming techniques

February 20, 2011 by hgpu

Optimization of HEP codes on GPUs

M. Al-Turany

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Tags: CUDA, High Energy Physics - Experiment, nVidia, nVidia GeForce 8400 GT, nVidia GeForce 8800 GT, nVidia GeForce GTX 480, nVidia Quadro NVS 290, Optimization, Physics, Tesla C1060

February 18, 2011 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

Gyrokinetic Particle-in-Cell Optimization on Emerging Multi- and Manycore Platforms

Speculative Execution on Multi-GPU Systems

Task management for irregular-parallel workloads on the GPU

Dynamic load balancing on single- and multi-GPU systems

Formal Description and Optimization Based High – Performance Computing on CUDA

Architecture-Aware Optimization Targeting Multithreaded Stream Computing

Automatic data movement and computation mapping for multi-level parallel architectures with explicitly managed memories

A Tuning Framework for Software-Managed Memory Hierarchies

Achieving a single compute device image in OpenCL for multiple GPUs

Data parallel loop statement extension to CUDA: GpuC

Program Optimization Study on a 128-Core GPU

Optimization of HEP codes on GPUs

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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