high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia GeForce GTX Titan V100

SOL: Effortless Device Support for AI Frameworks without Source Code Changes

Nicolas Weber, Felipe Huici

View

Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan V100, nVidia Quadro P 4000, PyTorch

March 29, 2020 by hgpu

Code generated HPC Kernels Using Llama-2-70b

Comparing Llama-2 and GPT-3 LLMs for HPC kernels generation

Scope is all you need: Transforming LLMs for HPC Code

Scope is all you need: Transforming LLMs for HPC Code

pocl - Portable Computing Language

PoCL-R: An Open Standard Based Offloading Layer for Heterogeneous Multi-Access Edge Computing with Server Side Scalability

HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

openCLDispatcher

Novel insights on atomic synchronization for sort-based group-by on GPUs

CEED Benchmarks

Performant low-order matrix-free finite element kernels on GPU architectures

Sieve: Stratified GPU-Compute Workload Sampling

Sieve: Stratified GPU-Compute Workload Sampling

EngineCL: Usability and Performance in Heterogeneous Computing

Mashing load balancing algorithm to boost hybrid kernels in molecular dynamics simulations

Ginkgo: high-performance linear algebra library for manycore systems

Porting Batched Iterative Solvers onto Intel GPUs with SYCL

AlphaFold2

APACE: AlphaFold2 and advanced computing as a service for accelerated discovery in biophysics

See all packages

* * *

* * *

HGPU group © 2010-2023 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: