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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

Solving Stochastic Differential Equations Using General Purpose Graphics Processing Unit

Lev Alexandrovich Neiman

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Tags: Algorithms, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 480, Package, Tesla C1060, Tesla C2075

April 28, 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

CUDA 2D Stencil Computations for the Jacobi Method

Jose Maria Cecilia, Jose Manuel Garcia, Manuel Ujaldon

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Differential equations, Linear Algebra, nVidia, Optimization, Tesla C1060, Tesla C870

March 16, 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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Tags: Computer science, CUDA, Differential equations, Distributed data structures, Linear Algebra, nVidia, Package, Partial differential equations, PDEs

March 16, 2012 by hgpu

Acceleration of Solving Maxwell’s Equations Using Cluster of GPUs

E. Arianyan, S. A. Motamedi, M. Hekmatpanah, I. Arianyan

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Tags: Algorithms, CUDA, Differential equations, Electrodynamics, FDTD, Finite difference, Finite-difference time-domain, Maxwell's equations, nVidia, nVidia GeForce 8400 GS

March 10, 2012 by hgpu

Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods

Tomas Oberhuber, Atsushi Suzuki, Jan Vacata, Vitezslav Zabka

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Tags: Algorithms, CUDA, Differential equations, Image processing, MRI, nVidia, nVidia GeForce GTX 480, ODEs, Ordinary differential equations, Partial differential equations, PDEs

February 22, 2012 by hgpu

Stochastic Differential Equations simulation using GPU

Narayana Darapaneni, Prakalp Somawanshi, Meghana Joshi

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Tags: Algorithms, Computer science, CUDA, Differential equations, Finance, Monte Carlo simulation, nVidia, nVidia GeForce GTX 275, Pseudo-random number generators, Stochastic simulation

February 7, 2012 by hgpu

An OpenCL implementation for the solution of TDSE on GPU and CPU architectures

Cathal O'Broin, Lampros A. A. Nikolopoulos

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Tags: Algorithms, ATI, ATI FirePro V7800, Computational Physics, Differential equations, nVidia, ODEs, OpenCL, Ordinary differential equations, Physics, Quantum Physics, Tesla S1070

January 31, 2012 by hgpu

A GPU-Based Implementation of Differential Evolution for Solving the Gene Regulatory Network Model Inference Problem

Luis E. Ramirez-Chavez, Carlos A. Coello Coello, Eduardo Rodriguez-Tello

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Tags: Bioinformatics, Biology, CUDA, Differential equations, Differential evolution, nVidia, nVidia GeForce GTX 460, Optimization

January 23, 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

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

Solving Stochastic Differential Equations Using General Purpose Graphics Processing Unit

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

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

CUDA 2D Stencil Computations for the Jacobi Method

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

Multi-platform Linear Algebra

Acceleration of Solving Maxwell’s Equations Using Cluster of GPUs

Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods

Stochastic Differential Equations simulation using GPU

An OpenCL implementation for the solution of TDSE on GPU and CPU architectures

A GPU-Based Implementation of Differential Evolution for Solving the Gene Regulatory Network Model Inference Problem

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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