high performance computing on graphics processing units: hgpu.org

Niels Drost, Jason Maassen, Maarten A.J. van Meersbergen, Henri E. Bal, F. Inti Pelupessy, Simon Portegies Zwart, Michael Kliphuis, Henk A. Dijkstra, Frank J. Seinstra

View

Download (PDF)

Tags: Astrophysics, Cloud, Computer science, CUDA, Earth and Space Sciences, Heterogeneous systems, nVidia, Physics, Solar and Stellar Astrophysics, Tesla C2050

March 6, 2012 by hgpu

Efficient Performance Evaluation of Memory Hierarchy for Highly Multithreaded Graphics Processors

Sara S. Baghsorkhi, Isaac Gelado, Matthieu Delahaye, Wen-mei W. Hwu

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Performance, Sparse matrix, Tesla C2050

March 2, 2012 by hgpu

Parallel Loopy Belief Propagation in Conditional Random Fields

Nico Piatkowski, Katharina Morik

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, Tesla C2050

March 1, 2012 by hgpu

Fast Multipole Methods and High Performance Computing

Cristopher Ratkevich Cecka

View

Download (PDF)

Source codes

Tags: CUDA, Electrodynamics, Fast multipole method, nVidia, Package, Tesla C1060, Tesla C2050, Thesis

February 26, 2012 by hgpu

Shredder: GPU-Accelerated Incremental Storage and Computation

Pramod Bhatotia, Rodrigo Rodrigues, Akshat Verma

View

Download (PDF)

Tags: Cloud, Computer science, CUDA, MapReduce, nVidia, Storage system, Tesla C2050

February 24, 2012 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Targeting heterogeneous architectures via macro data flow

Parallel Branch and Bound on a CPU-GPU System

A GPU Algorithm for Greedy Graph Matching

NUMA Data-Access Bandwidth Characterization and Modeling

Relational Algorithms for Multi-Bulk-Synchronous Processors

Dynamic Task-Scheduling and Resource Management for GPU Accelerators in Medical Imaging

Efficient Relational Algebra Algorithms and Data Structures for GPU

Efficient Performance Evaluation of Memory Hierarchy for Highly Multithreaded Graphics Processors

Parallel Loopy Belief Propagation in Conditional Random Fields

Fast Multipole Methods and High Performance Computing

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Most viewed papers (last 30 days)