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Stencil-Aware GPU Optimization of Iterative Solvers

Chekuri Choudary, Jeswin Godwin, Justin Holewinski, Deepan Karthik, Daniel Lowell, Azamat Mametjanov, Boyana Norris, Gerald Sabin, P. Sadayappan

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Tags: Computer science, CUDA, Differential equations, nVidia, Optimization, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070

July 11, 2012 by hgpu

GPU-based Assembly of Stiffness Matrices in the Parallel Multilevel Partition of Unity Method

Sebastian Kanis

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Tags: Differential equations, Mathematics, nVidia, nVidia GeForce GTX 560 Ti, Partial differential equations, PDEs, Thesis

July 5, 2012 by hgpu

Shallow Water Simulation on GPUs for Sparse Domains

Martin L. Saetra

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Tags: CUDA, Fluid dynamics, nVidia, Partial differential equations, PDEs

June 29, 2012 by hgpu

Autotuning Stencil-Based Computations on GPUs

Azamat Mametjanov, Daniel Lowell, Ching-Chen May, Boyana Norris

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Source codes

Tags: Computer science, CUDA, Differential equations, nVidia, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C1060, Tesla C2070

June 9, 2012 by hgpu

High Accuracy Gravitational Waveforms from Black Hole Binary Inspirals Using OpenCL

Justin McKennon, Gary Forrester, Gaurav Khanna

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Tags: ATI, ATI Radeon HD 7970, Differential equations, General Relativity and Quantum Cosmology, Gravitation, Gravitational waves, nVidia, OpenCL, Partial differential equations, PDEs, Physics, Tesla C2050

June 4, 2012 by hgpu

C-DAC’s Efforts – Application Kernels on HPC Cluster with GPU Accelerators

VCV.Rao, Nisha Agrawa, Samrit Maity

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Tags: AMD FirePro V5900, AMD FirePro V7900, AMD FireStream 9350, ATI, Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, MPI, nVidia, OpenCL, Partial differential equations, PDEs, Tesla C2060

May 19, 2012 by hgpu

Radiation Modeling Using the Uintah Heterogeneous CPU/GPU Runtime System

Alan Humphrey, Qingyu Meng, Martin Berzins, Todd Harman

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Tags: CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, MPI, nVidia, Partial differential equations, Pthreads, Task scheduling, Tesla M2090

May 11, 2012 by hgpu

High-performance sparse matrix-vector multiplication on GPUs for structured grid computations

Jeswin Godwin, Justin Holewinski, P. Sadayappan

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Tags: Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, Partial differential equations, PDEs, Sparse matrix, Tesla C2050

April 25, 2012 by hgpu

Paraiso : An Automated Tuning Framework for Explicit Solvers of Partial Differential Equations

Takayuki Muranushi

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Tags: Algorithms, Astrophysics, CUDA, Differential equations, Instrumentation and Methods for Astrophysics, nVidia, Package, Partial differential equations, PDEs, Tesla M2050

April 25, 2012 by hgpu

Impact of asynchronism on GPU accelerated parallel iterative computations

Sylvain Contassot-Vivier, Thomas Jost, Stephane Vialle

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, Partial differential equations, PDEs, Performance

March 22, 2012 by hgpu

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Dimitar Lukarski

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Tags: Algorithms, Computer science, CUDA, Differential equations, Factorization, FEM, Finite difference, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 580, Partial differential equations, PDEs, Sparse matrix, Tesla M1060, Tesla S1070, Thesis

March 16, 2012 by hgpu

Multi-platform Linear Algebra

E. Ketelaer, D. Lukarski

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Source codes

Tags: Computer science, CUDA, Differential equations, Distributed data structures, Linear Algebra, nVidia, Package, Partial differential equations, PDEs

March 16, 2012 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

Stencil-Aware GPU Optimization of Iterative Solvers

GPU-based Assembly of Stiffness Matrices in the Parallel Multilevel Partition of Unity Method

Shallow Water Simulation on GPUs for Sparse Domains

Autotuning Stencil-Based Computations on GPUs

High Accuracy Gravitational Waveforms from Black Hole Binary Inspirals Using OpenCL

C-DAC’s Efforts – Application Kernels on HPC Cluster with GPU Accelerators

Radiation Modeling Using the Uintah Heterogeneous CPU/GPU Runtime System

High-performance sparse matrix-vector multiplication on GPUs for structured grid computations

Paraiso : An Automated Tuning Framework for Explicit Solvers of Partial Differential Equations

Impact of asynchronism on GPU accelerated parallel iterative computations

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Multi-platform Linear Algebra

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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