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Accelerating exotic option pricing and model calibration using GPUs

Andre Bernemann, Ralph Schreyer, Klaus Spanderen

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Tags: CUDA, Finance, GPU cluster, Monte Carlo simulation, nVidia, Tesla C1060

October 21, 2011 by hgpu

Hard-Sphere Collision Simulations with Multiple GPUs, PCIe Extension Buses and GPU-GPU Communications

K.A. Hawick, D.P.Playne

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Tags: Algorithms, CUDA, GPU cluster, Gravitation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Physics, Tesla C2050, Tesla C2070

October 16, 2011 by hgpu

Asynchronous Communication for Finite-Difference Simulations on GPU Clusters using CUDA and MPI

D.P. Playne, K.A. Hawick

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Tags: Algorithms, Computer science, CUDA, GPU cluster, MPI, Numerical simulation, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480

October 16, 2011 by hgpu

Operating Systems Challenges for GPU Resource Management

Shinpei Kato, Scott Brandt, Yutaka Ishikawa, Ragunathan (Raj) Rajkumar

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Tags: Computer science, CUDA, GPU cluster, nVidia, OpenCL, Operating systems, Virtualization

October 15, 2011 by hgpu

Towards Utilizing Remote GPUs for CUDA Program Execution

Xiaonan Ji, Spencer Davis, Erikson Hardesty, Xu Liang, Sabuj Saha, Hai Jiang

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Networks, nVidia

October 15, 2011 by hgpu

GPU Computing Gems: Jade Edition

Wen-mei W. Hwu

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Tags: Algorithms, Book, Cellular automata, Computational finance, Computer science, Computer vision, CUDA, Finance, Fluid dynamics, Games, GPU cluster, nVidia

October 14, 2011 by hgpu

State of The Art Report on GPU

Rita Borgo, Ken Brodlie

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Tags: Computer science, CUDA, DirectX, GLSL, GPU cluster, Hardware, HLSL, Larrabee, nVidia, OpenGL, Programming techniques, Review

October 13, 2011 by hgpu

Astrophysical particle simulations with large custom GPU clusters on three continents

K. R. Spurzem, P. Berczik, T. Hamada, K. Nitadori, G. Marcus, A. Kugel, R. Manner, I. Berentzen, J. Fiestas, R. Banerjee, R. Klessen,

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Tags: Astrophysics, GPU cluster, N-body simulation

October 8, 2011 by hgpu

Exploring The Latency and Bandwidth Tolerance of CUDA Applications

Gregory Diamos, Sudnya Padalikar

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Tags: Benchmarking, Computer science, CUDA, GPU cluster, Memory, nVidia, Performance, PTX, Tesla C1060

September 30, 2011 by hgpu

Large-Scale High-Lundquist Number Reduced MHD Simulations of the Solar Corona Using GPU Accelerated Machines

L. Lin, Chung-Sang Ng, A. Bhattacharjee

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Tags: Astrophysics, Computational Physics, CUDA, GPU cluster, Instrumentation and Methods for Astrophysics, Magnetohydrodynamics, MPI, nVidia, Plasma physics, Solar and Stellar Astrophysics, Spectral methods, Tesla C2050

September 29, 2011 by hgpu

Fast analysis of molecular dynamics trajectories with graphics processing units-Radial distribution function histogramming

Benjamin G. Levine, John E. Stone, Axel Kohlmeyer

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Tags: Algorithms, Chemistry, CUDA, GPU cluster, Heterogeneous systems, Molecular dynamics, nVidia, nVidia GeForce GTX 480, Visualization

September 21, 2011 by hgpu

The TheLMA project: Multi-GPU implementation of the lattice Boltzmann method

Christian Obrecht, Frederic Kuznik, Bernard Tourancheau, Jean-Jacques Roux

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Tags: CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, nVidia, Presentation, Tesla C1060

September 19, 2011 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Accelerating exotic option pricing and model calibration using GPUs

Hard-Sphere Collision Simulations with Multiple GPUs, PCIe Extension Buses and GPU-GPU Communications

Asynchronous Communication for Finite-Difference Simulations on GPU Clusters using CUDA and MPI

Operating Systems Challenges for GPU Resource Management

Towards Utilizing Remote GPUs for CUDA Program Execution

GPU Computing Gems: Jade Edition

State of The Art Report on GPU

Astrophysical particle simulations with large custom GPU clusters on three continents

Exploring The Latency and Bandwidth Tolerance of CUDA Applications

Large-Scale High-Lundquist Number Reduced MHD Simulations of the Solar Corona Using GPU Accelerated Machines

Fast analysis of molecular dynamics trajectories with graphics processing units-Radial distribution function histogramming

The TheLMA project: Multi-GPU implementation of the lattice Boltzmann method

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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