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Accelerating In-Memory Graph Database traversal using GPGPUS

Ashwin Raghav Mohan Ganesh

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Tags: Computer science, CUDA, Databases, nVidia, Package

May 25, 2012 by hgpu

Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs

Rohit Sinha, Aayush Prakash, Hiren D. Patel

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Tags: Computer science, CUDA, nVidia, Tesla C2075

May 25, 2012 by hgpu

Java on CUDA architecture

Jan Strnad

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Tags: Computer science, CUDA, Image processing, Java, Linear Algebra, Matrix multiplication, nVidia, Thesis

May 24, 2012 by hgpu

Sparse direct solvers with accelerators over DAG runtimes

Xavier Lacoste, Pierre Ramet, Mathieu Faverge, Yamazaki Ichitaro, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Sparse direct solvers, Tesla T20

May 24, 2012 by hgpu

Tuning a Finite Difference Computation for Parallel Vector Processors

Gerhard Zumbusch

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Tags: Algorithms, Computer science, Finite difference, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 480, nVidia GeForce GTX 680, OpenCL, Performance

May 24, 2012 by hgpu

Compiler optimizations for directive-based programming for accelerators

Matias Piispanen

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Optimization

May 24, 2012 by hgpu

Fine-Grained Resource Sharing for Concurrent GPGPU Kernels

Chris Gregg, Jonathan Dorn, Kim Hazelwood, Kevin Skadron

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Tags: Computer science, nVidia, nVidia GeForce GTX 460, OpenCL, Programming techniques, Task scheduling

May 24, 2012 by hgpu

GMProf: A Low-Overhead, Fine-Grained Profiling Approach for GPU Programs

Mai Zheng, Vignesh T. Ravi, Wenjing Ma, Feng Qin, Gagan Agrawal

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

May 23, 2012 by hgpu

Investigating Warp Size Impact in GPUs

Ahmad Lashgar, Amirali Baniasadi, Ahmad Khonsari

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Tags: Computer science, Hardware Architecture

May 23, 2012 by hgpu

Adaptive fast multipole methods on the GPU

Anders Goude, Stefan Engblom

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Tags: Computer science, CUDA, Data Structures and Algorithms, Fast multipole method, nVidia, Package, Tesla C2075

May 23, 2012 by hgpu

Self-Tuning Distribution of DB-Operations on Hybrid CPU/GPU Platforms

Sebastian Bress, Siba Mohammad, Eike Schallehn

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia

May 20, 2012 by hgpu

High-Level Support for Pipeline Parallelism on Many-Core Architectures

Siegfried Benkner, Enes Bajrovic, Erich Marth, Martin Sandrieser, Raymond Namyst, Samuel Thibault

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480

May 20, 2012 by hgpu

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

PyOMP: OpenMP for Python in Numba

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Accelerating In-Memory Graph Database traversal using GPGPUS

Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs

Java on CUDA architecture

Sparse direct solvers with accelerators over DAG runtimes

Tuning a Finite Difference Computation for Parallel Vector Processors

Compiler optimizations for directive-based programming for accelerators

Fine-Grained Resource Sharing for Concurrent GPGPU Kernels

GMProf: A Low-Overhead, Fine-Grained Profiling Approach for GPU Programs

Investigating Warp Size Impact in GPUs

Adaptive fast multipole methods on the GPU

Self-Tuning Distribution of DB-Operations on Hybrid CPU/GPU Platforms

High-Level Support for Pipeline Parallelism on Many-Core Architectures

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

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

SW#SYCL

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

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

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

PyOMP: OpenMP for Python in Numba

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