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The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing

Blesson Varghese

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Tags: Computational Engineering, Computer science, CUDA, Finance, Intel Xeon Phi, nVidia, Performance, Tesla C2075

January 28, 2015 by hgpu

Global finite element matrix construction based on a CPU-GPU implementation

Francisco Javier Ramírez-Gil, Marcos de Sales Guerra Tsuzuki, Wilfredo Montealegre-Rubio

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Tags: Analysis of PDEs, Computational Engineering, CUDA, FEM, Numerical Analysis, parallel computing, PDEs, Performance

January 21, 2015 by fjramireg

Performance Engineering of the Kernel Polynomial Method on Large-Scale CPU-GPU Systems

Moritz Kreutzer, Georg Hager, Gerhard Wellein, Andreas Pieper, Andreas Alvermann, Holger Fehske

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Tags: Computational Engineering, CUDA, Finance, Mesoscale and Nanoscale Physics, nVidia, Tesla K20

October 22, 2014 by hgpu

Accounting for Secondary Uncertainty: Efficient Computation of Portfolio Risk Measures on Multi and Many Core Architectures

Blesson Varghese, Andrew Rau-Chaplin

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Tags: Computational Engineering, Computer science, CUDA, Finance, nVidia, Risk Management, Tesla C2075

October 10, 2013 by hgpu

Parallel Simulations for Analysing Portfolios of Catastrophic Event Risk

Aman Bahl, Oliver Baltzer, Andrew Rau-Chaplin, Blesson Varghese

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Tags: Algorithms, Computational Engineering, Computer science, CUDA, Finance, Monte Carlo simulation, nVidia, Stochastic simulation, Tesla C2075

August 12, 2013 by hgpu

Scalable Techniques for Scheduling and Mapping DSP Applications onto Embedded Multiprocessor Platforms

George Zaki

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Tags: Algorithms, Code generation, Computational Engineering, CUDA, Data parallelism, DSP, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, Signal processing, Thesis

July 12, 2013 by hgpu

ClusCo: clustering and comparison of protein models

Jamroz Michal, Kolinski Andrzej

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Source codes

Tags: Biology, Biomolecules, Clustering, Computational Engineering, CUDA, Finance, nVidia, nVidia GeForce GTX 470, Package

February 20, 2013 by hgpu

Parallel Computing of Discrete Element Method on GPU

Teruyoshi Washizawa, Yasuhiro Nakahara

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Tags: Computational Engineering, Computer science, CUDA, nVidia, OpenCL, Tesla C2050

January 11, 2013 by hgpu

Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

Jose M. Dominguez, Alejandro J.C. Crespo, Moncho Gomez-Gesteira

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Tags: Computational Engineering, Computer science, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 480, OpenMP, Optimization, Performance, Tesla C1060

October 18, 2011 by hgpu

Potential contribution of CNN-based solving of stiff ODEs and PDEs to enabling real-time Computational Engineering

J.C. Chedjou, K. Kyamakya, U.A. Khan, M.A. Latif

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Tags: Cellular neural networks, CNN, Computational Engineering, Computer science, Differential equations, DSP, FPGA, Maxwell's equations, Neural networks, ODEs, Optimization, Ordinary differential equations, Partial differential equations, PDEs

August 2, 2011 by hgpu

Potential of General Purpose Graphic Processing Unit for Energy Management System

Jean-Charles Tournier, Vaibhav Donde, Zhao Li

Tags: Computational Engineering, Computer science, Power Systems Simulation, Sparse linear iterative solvers

June 16, 2011 by hgpu

A GPU based Algorithm for Determining the Optimal Cutting Direction in Deep Mold Machining

K. Morimoto, M. Inui

Tags: Algorithms, Computational Engineering, Rendering

May 23, 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_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

See all packages

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high performance computing on graphics processing units: hgpu.org

The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing

Global finite element matrix construction based on a CPU-GPU implementation

Performance Engineering of the Kernel Polynomial Method on Large-Scale CPU-GPU Systems

Accounting for Secondary Uncertainty: Efficient Computation of Portfolio Risk Measures on Multi and Many Core Architectures

Parallel Simulations for Analysing Portfolios of Catastrophic Event Risk

Scalable Techniques for Scheduling and Mapping DSP Applications onto Embedded Multiprocessor Platforms

ClusCo: clustering and comparison of protein models

Parallel Computing of Discrete Element Method on GPU

Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

Potential contribution of CNN-based solving of stiff ODEs and PDEs to enabling real-time Computational Engineering

Potential of General Purpose Graphic Processing Unit for Energy Management System

A GPU based Algorithm for Determining the Optimal Cutting Direction in Deep Mold Machining

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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