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Collaborative execution environment for heterogeneous parallel systems

Aleksandar Ilic, Leonel Sousa

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Tags: Computer science, CUBLAS, CUDA, Data parallelism, FFT, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Presentation

August 28, 2011 by hgpu

Global Illumination for Advanced Computer Graphics

M. Robart, S. Hill, E. Tanguy

Tags: 3D Graphics and Realism, Algorithms, Computer science, Overview, Rasterization, Raytracing, Rendering

August 28, 2011 by hgpu

Switching to High Gear: Opportunities for Grand-Scale Real-Time Parallel Simulations

Kalyan S. Perumalla

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Tags: Computer science, CUDA, MPI, nVidia, Performance, Review

August 27, 2011 by hgpu

directCell: hybrid systems with tightly coupled accelerators

H. Penner, U. Bacher, J. Kunigk, C. Rund, H. J. Schick

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Tags: Cell processor, Computer science, Hybrid computing, Performance

August 27, 2011 by hgpu

A breadth-first course in multicore and manycore programming

Suzanne Rivoire

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Tags: Computer science, CUDA, High-level Languages, nVidia, OpenMP, Programming techniques

August 27, 2011 by hgpu

A structured parallel periodic arnoldi shooting algorithm for RF-PSS analysis based on GPU platforms

Xue-Xin Liu, Hao Yu, Jacob Relles, Sheldon X.-D. Tan

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Tags: Algorithms, CAD, Computer science, CUDA, Numerical Analysis, nVidia, Performance, Tesla C1060

August 27, 2011 by hgpu

Automatic contention detection and amelioration for data-intensive operations

John Cieslewicz, Kenneth A. Ross, Kyoho Satsumi, Yang Ye

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Tags: Computer science, Databases, Performance

August 27, 2011 by hgpu

Fast and sleek glyph rendering for interactive HARDI data exploration

T.H.J.M. Peeters, V. Prckovska, M. van Almsick, A. Vilanova, B.M. ter Haar Romeny

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Tags: 3D Graphics and Realism, Computer science, Diffusion tensor, Magnetic resonance imaging, MRI, nVidia, nVidia GeForce 8800 GTX, Probability, Rendering, Visualization

August 27, 2011 by hgpu

Parallel Fast Gauss Transform

Rahul S. Sampath, Hari Sundar, Shravan K. Veerapaneni

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Tags: Algorithms, Computer science, Performance

August 26, 2011 by hgpu

PFunc: modern task parallelism for modern high performance computing

Prabhanjan Kambadur, Anshul Gupta, Amol Ghoting, Haim Avron, Andrew Lumsdaine

Tags: Computer science, Package, Performance, Programming techniques, Software Engineering

August 26, 2011 by hgpu

Challenging cloning related problems with GPU-based algorithms

Thierry Lavoie, Michael Eilers-Smith, Ettore Merlo

Tags: Computer science, Software Engineering, String matching

August 26, 2011 by hgpu

Considerations when evaluating microprocessor platforms

Michael Anderson, Bryan Catanzaro, Jike Chong, Ekaterina Gonina, Kurt Keutzer, Chao-Yue Lai, Mark Murphy, David Sheffield, Bor-Yiing Su, Narayanan Sundaram

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Tags: Computer science, Performance, Review

August 26, 2011 by hgpu

Matrix multiplication using Tensor Cores in CUDA

Utilizing Tensor Cores in Futhark

CPP Joules: Energy Measurement tool for CPP/CUDA programs

CPPJoules: An Energy Measurement Tool for C++

HPC-Coder-v2

HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

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