high performance computing on graphics processing units: hgpu.org

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Specification and verification of GPGPU programs

Stefan Blom, Marieke Huisman and Matej Mihelcic

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Tags: Computer science, OpenCL, Programming techniques

November 18, 2013 by hgpu

Performance analysis of SSE instructions in multi-core CPUs and GPU computing on FDTD scheme for solid and fluid vibration problems

Jorge Frances Monllor, Sergio Bleda Perez, Andres Marquez Ruiz, Cristian Neipp Lopez, Sergi Gallego Rico, Beatriz Otero Calvino, Augusto Belendez Vazquez

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Tags: CUDA, FDTD, Finite-difference time-domain, Fluid dynamics, nVidia, nVidia GeForce GTX 470, Programming techniques

September 15, 2013 by hgpu

A Bi-objective Optimization Framework for Query Plans

P. Przymus, K. Kaczmarski, K. Stencel

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Tags: Heterogeneous systems, Performance, Programming techniques

September 7, 2013 by hgpu

Accurate Analytic Models to Estimate Execution Time on GPU Applications

Pedro Velho, Daniel A. G. de Oliveira, Edson L. Padoin, Philippe O. A. Navaux

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance, Programming techniques

August 21, 2013 by hgpu

Portable HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi

Jack Dongarra, Mark Gates, Azzam Haidar, Yulu Jia, Khairul Kabir, Piotr Luszczek, Stanimire Tomov

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Tags: Computer science, Heterogeneous systems, Intel Phi, Linear Algebra, Package, Programming techniques

July 30, 2013 by hgpu

Megakernels Considered Harmful: Wavefront Path Tracing on GPUs

Samuli Laine, Tero Karras, Timo Aila

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, Programming techniques, Raytracing, Tesla K20

June 19, 2013 by hgpu

Accelerated Dynamic Programming on GPU: A Study of Speed Up and Programming Approach

Mohsin Altaf Wani, S.M.K Quadri

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 570, Optimization, Programming techniques

June 8, 2013 by hgpu

Modernizing the core quantum chemistry algorithms

Andrey Asadchev

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Tags: Algorithms, Chemistry, Computational chemistry, CUDA, nVidia, Programming techniques, Tesla C2050, Thesis

June 8, 2013 by hgpu

Parallelization & checkpointing of GPU applications through program transformation

Lizandro Damian Solano-Quinde

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Tags: Computer science, nVidia, OpenCL, Programming techniques, Tesla C2070, Tesla T10, Thesis

June 6, 2013 by hgpu

Effects of Concurrency Techniques and Algorithm Performance: A Comparative Analysis of Single-Threaded, Multi-Threaded, and GPGPU Programming Techniques

Joshua Penton

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Tags: ATI, ATI Radeon HD 6750 M, Computer science, FFT, Java, OpenCL, Package, Performance, Programming techniques

May 28, 2013 by hgpu

Graphics processing unit (GPU) programming strategies and trends in GPU computing

Andre R. Brodtkorb, Trond R. Hagen, Martin L. Saetra

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Tags: Computer science, Heterogeneous systems, Metaheuristics, Optimization, Overview, Programming techniques

April 19, 2013 by hgpu

SemCache: Semantics-aware Caching for Efficient GPU Offloading

Nabeel AlSaber, Milind Kulkarni

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques, Tesla C2070

April 19, 2013 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

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high performance computing on graphics processing units: hgpu.org

Specification and verification of GPGPU programs

Performance analysis of SSE instructions in multi-core CPUs and GPU computing on FDTD scheme for solid and fluid vibration problems

A Bi-objective Optimization Framework for Query Plans

Accurate Analytic Models to Estimate Execution Time on GPU Applications

Portable HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi

Megakernels Considered Harmful: Wavefront Path Tracing on GPUs

Accelerated Dynamic Programming on GPU: A Study of Speed Up and Programming Approach

Modernizing the core quantum chemistry algorithms

Parallelization & checkpointing of GPU applications through program transformation

Effects of Concurrency Techniques and Algorithm Performance: A Comparative Analysis of Single-Threaded, Multi-Threaded, and GPGPU Programming Techniques

Graphics processing unit (GPU) programming strategies and trends in GPU computing

SemCache: Semantics-aware Caching for Efficient GPU Offloading

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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