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Early Experiences Running the 3D Stencil Jacobi Method in Intel Xeon Phi

Mario Hernandez, Jose M. Garcia, Jose M. Cecilia

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Tags: Computer science, Intel Xeon Phi, Physics, Stencil computation

April 8, 2015 by hgpu

OmpSs task offload

Florentino Sainz

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Tags: Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, MPI, nVidia, OpenCL, Tesla K20, Thesis

April 4, 2015 by hgpu

Separable projection integrals for higher-order correlators of the cosmic microwave sky: Acceleration by factors exceeding 100

J. Briggs, J. Jaykka, J. R. Fergusson, E. P. S. Shellard, S. J. Pennycook

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Tags: Astrophysics, Computer science, Intel Xeon Phi, MPI, OpenMP

April 1, 2015 by hgpu

Evaluating kernels on Xeon Phi to accelerate Gysela application

G. Latu, M. Haefele, J. Bigot, V. Grandgirard, T. Cartier-Michaud, F. Rozar

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Tags: Computational Physics, Intel Xeon Phi, Physics

March 22, 2015 by hgpu

CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication

Weifeng Liu, Brian Vinter

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Tags: Algorithms, AMD Radeon R9 290X, Benchmarking, Computer science, CUDA, Intel Xeon Phi, Mathematical Software, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Performance, Sparse matrix

March 20, 2015 by hgpu

Iris Matching Algorithm on Many-Core Platforms

Chen Liu, Benjamin Petroski, Guthrie Cordone, Gildo Torres, Stephanie Schuckers

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Tags: Algorithms, Biometrics, Computer science, Computer vision, CUDA, Intel Xeon Phi, nVidia, nVidia GeForce GTS 450

March 2, 2015 by hgpu

Evaluating Performance Portability of OpenACC

Amit Sabne, Putt Sakdhnagool, Seyong Lee, Jeffrey S. Vetter

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 680, OpenACC

March 2, 2015 by hgpu

Accelerating Lagrangian Particle Dispersion in the Atmosphere with OpenCL across Multiple Platforms

Paul Harvey, Saji Hameed, Wim Vanderbauwhede

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Tags: AMD Radeon R9 290X, ATI, CUDA, Earth and Space Sciences, Intel Xeon Phi, nVidia, nVidia GeForce GTX 580, OpenCL, Tesla C2075, Tesla K20, Weather prediction

February 24, 2015 by hgpu

Investigation of the OpenCL SYCL Programming Model

Angelos Trigkas

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, OpenCL, Thesis

February 23, 2015 by hgpu

QPACE 2 and Domain Decomposition on the Intel Xeon Phi

Paul Arts, Jacques Bloch, Peter Georg, Benjamin Glaessle, Simon Heybrock, Yu Komatsubara, Robert Lohmayer, Simon Mages, Bernhard Mendl, Nils Meyer, Alessio Parcianello, Dirk Pleiter, Florian Rappl, Mauro Rossi, Stefan Solbrig, Giampietro Tecchiolli, Tilo Wettig, Gianpaolo Zanier

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Tags: Benchmarking, Computational Physics, Computer science, High Energy Physics - Lattice, Intel Xeon Phi

February 22, 2015 by hgpu

Fine-Tuning Vectorization and Memory Traffic on Intel Xeon Phi Coprocessors: LU Decomposition of Small Matrices

Andrey Vladimirov

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Tags: cache, Intel Xeon Phi, Ivy Bridge, Package

February 9, 2015 by Andrey Vladimirov

Comparison of OpenCL performance on different platforms using VexCL and Blaze

Hammad Mazhar, Dan Negrut

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Tags: AMD Radeon R7 260, ATI, Benchmarking, Computer science, Intel Xeon Phi, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 770, OpenCL, Performance, Sparse matrix, Tesla K20

February 6, 2015 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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