high performance computing on graphics processing units: hgpu.org

hgpu.org » Optimization

Designing OP2 for GPU architectures

M.B. Giles, G.R. Mudalige, B. Spencer, C. Bertolli, I. Reguly

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Tags: Computer science, nVidia, nVidia GeForce GTX 560 Ti, Optimization, Package, Performance, Tesla C2070

August 11, 2012 by hgpu

Large Scale Monte Carlo Tree Search on GPU

Kamil Marek Rocki

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Games, nVidia, Optimization, Search, Tesla C2050, Thesis

August 11, 2012 by hgpu

Optimizing Memory-Bound Numerical Kernels on GPU Hardware Accelerators

Ahmad Abdelfattah, Jack Dongarra, David Keyes, Hatem Ltaief

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Tags: Computer science, CUBLAS, CUDA, nVidia, Optimization, Package, Tesla C2070

August 10, 2012 by hgpu

Fine-Granular Parallel EBCOT and Optimization with CUDA for Digital Cinema Image Compression

Fang Wei, Qiu Cui, Ye Li

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Tags: Algorithms, Compression, CUDA, Image processing, JPEG2000, nVidia, nVidia GeForce GT 240, Optimization

August 10, 2012 by hgpu

Optimizing Data Warehousing Applications for GPUs Using Kernel Fusion/Fission

Haicheng Wu, Gregory Diamos, Ashwin Lele, Jin Wang, Srihari Cadambi, Sudhakar Yalamanchili, Srimat Chakradhar

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Tags: Compilers, Computer science, CUDA, Databases, nVidia, Optimization, Tesla C2070

August 9, 2012 by hgpu

Solving the Flexible Job Shop Problem on Multi-GPU

Wojciech Bozejko, Zdzilaw Hejducki, Mariusz Uchronski, Mieczyslaw Wodecki

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Tags: Computer science, CUDA, GPU cluster, Metaheuristics, MPI, nVidia, Optimization, Search, Tesla S2050

August 8, 2012 by hgpu

Policy-based Tuning for Performance Portability and Library Co-optimization

Duane Merrill, Michael Garland, Andrew Grimshaw

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce 9800 GTX, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Performance

August 8, 2012 by hgpu

Dynamic Overset Grid Computations for CFD Applications on Graphics Processing Units

D. Chandar, J. Sitaraman, D. Mavriplis

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Tags: CUDA, Fluid dynamics, nVidia, Optimization, Tesla C2050, Tesla C2070

July 22, 2012 by hgpu

CUSIMANN: An optimized simulated annealing software for GPUs

Ana Maria Ferreiro Ferreiro, Jose Antonio Garcia Rodriguez, Jose German Lopez Salas, Carlos Vazquez Cendon

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Tags: Algorithms, Computer science, CUDA, nVidia, Optimization, Package

July 17, 2012 by hgpu

Sparse Matrix Matrix Multiplication on Hybrid CPU+GPU Platforms

Kiran Kumar Matam, Siva Rama Krishna Bharadwaj, Kishore Kothapalli

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, Optimization, Sparse matrix, Tesla C2050

July 16, 2012 by hgpu

A Yoke of Oxen and a Thousand Chickens for Heavy Lifting Graph Processing

Abdullah Gharaibeh, Lauro Beltrao Costa, Elizeu Santos-Neto, Matei Ripeanu

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Tags: Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, Optimization, Performance, Programming Languages, Programming techniques, Tesla C2050

July 16, 2012 by hgpu

Stencil-Aware GPU Optimization of Iterative Solvers

Chekuri Choudary, Jeswin Godwin, Justin Holewinski, Deepan Karthik, Daniel Lowell, Azamat Mametjanov, Boyana Norris, Gerald Sabin, P. Sadayappan

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Tags: Computer science, CUDA, Differential equations, nVidia, Optimization, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070

July 11, 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

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high performance computing on graphics processing units: hgpu.org

Designing OP2 for GPU architectures

Large Scale Monte Carlo Tree Search on GPU

Optimizing Memory-Bound Numerical Kernels on GPU Hardware Accelerators

Fine-Granular Parallel EBCOT and Optimization with CUDA for Digital Cinema Image Compression

Optimizing Data Warehousing Applications for GPUs Using Kernel Fusion/Fission

Solving the Flexible Job Shop Problem on Multi-GPU

Policy-based Tuning for Performance Portability and Library Co-optimization

Dynamic Overset Grid Computations for CFD Applications on Graphics Processing Units

CUSIMANN: An optimized simulated annealing software for GPUs

Sparse Matrix Matrix Multiplication on Hybrid CPU+GPU Platforms

A Yoke of Oxen and a Thousand Chickens for Heavy Lifting Graph Processing

Stencil-Aware GPU Optimization of Iterative Solvers

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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