high performance computing on graphics processing units: hgpu.org

R. Ammendola, A. Biagioni, L. Deri, M. Fiorini, O. Frezza, G. Lamanna, F. Lo Cicero, A. Lonardo, A. Messina, M. Sozzi, F. Pantaleo, P.S. Paolucci, D. Rossetti, F. Simula, L. Tosoratto, P. Vicini

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Tags: CUDA, Data acquisition, High Energy Physics - Experiment, nVidia, nVidia GeForce GTX 680, Physics, Tesla C1060, Tesla C2050

January 14, 2014 by hgpu

Implementations of the Hough Transform on the Embedded Multicore Processors

Xin Zhou, Norihiro Tomagou, Yasuaki Ito, Koji Nakano

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Tags: CUDA, DSP, FPGA, Image processing, nVidia, nVidia GeForce GTX 680

January 11, 2014 by hgpu

Architecting an LTE Base Station with Graphics Processing Units

Q. Zheng, Y. Chen, R. Dreslinski, C. Chakrabarti, A. Anastasopoulos, S. Mahlke, T. Mudge

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Wireless baseband architecture

December 21, 2013 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

Auto-Tuning Dedispersion for Many-Core Accelerators

Resolution of Linear Algebra for the Discrete Logarithm Problem using GPU and Multi-core Architectures

Work-Efficient Parallel GPU Methods for Single-Source Shortest Paths

Towards Efficient Risk Quantification-Using GPUs and Variance Reduction Technique

Comparing the Performance of Different x86 SIMD Instruction Sets for a Medical Imaging Application on Modern Multi- and Manycore Chips

GPU-Accelerated BWT Construction for Large Collection of Short Reads

Platform-Specific Optimization and Mapping of Stencil Codes through Refinement

Performance Evaluation of the Intel Many Integrated Core Architecture for 3D Image Reconstruction in Computed Tomography

Finite differences numerical method for two-dimensional superlattice Boltzmann transport equation and case comparison of CPU(C) and GPGPU(CUDA) implementations

GPUs for real-time processing in HEP trigger systems

Implementations of the Hough Transform on the Embedded Multicore Processors

Architecting an LTE Base Station with Graphics Processing Units

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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