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A capabilities-aware framework for using computational accelerators in data-intensive computing

M. Mustafa Rafique, Ali R. Butta, Dimitrios S. Nikolopoulos

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Tags: Cell processor, Cloud, Computer science, CUDA, GPU cluster, Heterogeneous systems, MapReduce, nVidia, nVidia GeForce 9600 M GT, Playstation

November 14, 2011 by hgpu

Exploiting Heterogeneity for Energy Efficiency in Chip Multiprocessors

V. Saripalli, G. Sun, A. Mishra, Y. Xie, S. Datta, V. Narayanan

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Tags: Computer science, Energy-efficient computing, Heterogeneous systems

November 12, 2011 by hgpu

Multithread Content Based File Chunking System in CPU-GPGPU Heterogeneous Architecture

Zhi Tang, Youjip Won

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 460

November 12, 2011 by hgpu

Creating HW/SW co-designed MPSoPC’s from high level programming models

Eugene Cartwright, Sen Ma, David Andrews, Miaoqing Huang

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, Operating systems, Pthreads

November 12, 2011 by hgpu

A translator framework for Dynamic Programming problems

Alejandro Acosta, Francisco Almeida, Ignacio Pelaez

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Tags: Algorithms, Compilers, Computer science, Heterogeneous systems

November 12, 2011 by hgpu

Compiling for a heterogeneous vector image processor

Fabien Coelho, Francois Irigoin

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Tags: Compilers, Heterogeneous systems, Image processing

November 12, 2011 by hgpu

Many-body quantum chemistry on graphics processing units

A. Eugene DePrince III, Jeff R. Hammond, Stephen K. Gray

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Tags: Algorithms, Chemistry, Computational chemistry, CUDA, Heterogeneous systems, Matrix multiplication, Molecular modeling, nVidia, Tesla C2050

November 11, 2011 by hgpu

Automatic transformation and optimization of applications on GPUs and GPU clusters

Wenjing Ma

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Tags: Algorithm optimization, Algorithms, Benchmarking, Code generation, Computer science, CUDA, Data mining, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GX2, Optimization, Tesla T10, Thesis

November 9, 2011 by hgpu

GPU Cluster with MATLAB

A. Guillen, M. Garcia, L. J. Herrera, H. Pomares, I. Rojas

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, Nearest neighbour, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GTX, nVidia GeForce GTS 450

November 8, 2011 by hgpu

High-Level Design for FPGA-based Multiprocessor Accelerators

Diana Gohringer, Matthias Birk, Michael Hubner, Jurgen Becker

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Tags: Computer science, FPGA, Heterogeneous systems, Programming techniques

November 7, 2011 by hgpu

Functional Programming for High-Performance Computing on Heterogeneous Architectures

Sylvain Henry

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Optimization, Performance, Programming Languages, Programming techniques

November 7, 2011 by hgpu

Keeneland: Bringing heterogeneous GPU computing to the computational science community

Jeffrey S. Vetter, Richard Glassbrook, Jack Dongarra, Karsten Schwan, Bruce Loftis, Stephen McNally, Jeremy Meredith, James Rogers, Philip Roth Kyle Spafford, Sudhakar Yalamanchili

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Tags: Computer science, Hardware Architecture, Heterogeneous systems, nVidia, Tesla M2070

November 7, 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 plugin for PySCF

Python-Based Quantum Chemistry Calculations with GPU Acceleration

QArray

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

Celerity: High-level C++ for Accelerator Clusters

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

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

Parallel Gaussian process with kernel approximation in CUDA

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