high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia GeForce GT 540

Data parallel patterns on CPU/GPU mix

T. Serban, M. Danelutto, M. Coppola

View

Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GT 540, nVidia GeForce GTX 285, Tesla C2050

January 22, 2013 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP-AMD: Extending CUDA to AMD Platforms

Kernel Tuner

Testing and Mutation Testing for GPU Kernels

GT4Py: GridTools for Python

GT4Py: High Performance Stencils for Weather and Climate Applications using Python

miniBUDE: A BUDE virtual-screening benchmark, in many programming models

Evaluation of FPGA-based high performance computing platforms

gossip: Efficient Communication Primitives for Multi-GPU Systems

Accelerating bioinformatics applications on CUDA-enabled multi-GPU systems

AUCMEDI: a framework for Automated Classification of Medical Images

Frameworks in Medical Image Analysis with Deep Neural Networks

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

AFOCL: Portable OpenCL Programming of FPGAs via Automated Built-in Kernel Management

AFOCL: Portable OpenCL Programming of FPGAs via Automated Built-in Kernel Management

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

pp-template: Template for Performance-Portable code development, targeting HOST-DEVICE computer architectures

An approach to performance portability through generic programming

See all packages

* * *

* * *

HGPU group © 2010-2023 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: