high performance computing on graphics processing units: hgpu.org

hgpu.org » SYCL

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

Yanwen Xu, Ang Li, Tyler Sorensen

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, CUDA, FPGA, Heterogeneous systems, HLS, Intel UHD 630, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson Nano, Package, Performance, SYCL

May 7, 2023 by hgpu

Fuzzing Loop Optimizations in Compilers for C++ and Data-Parallel Languages

Vsevolod Livinskii, Dmitry Babokin, John Regehr

View

Download (PDF)

Source codes

Tags: Code generation, Compilers, Computer science, oneAPI, Package, SYCL

April 23, 2023 by hgpu

Understanding Performance Portability of Bioinformatics Applications in SYCL on an NVIDIA GPU

Zheming Jin, Jeffrey S. Vetter

View

Download (PDF)

Source codes

Tags: Benchmarking, Bioinformatics, Computer science, CUDA, Heterogeneous systems, nVidia, Package, performance portability, SYCL, Tesla V100

April 16, 2023 by hgpu

Managing heterogeneous device memory using C++17 memory resources

S.N. Swatman, A. Krasznahorkay, P. Gessinger

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, HIP, Memory model, nVidia, Package, SYCL

April 2, 2023 by hgpu

Comparing SYCL data transfer strategies for tracking use cases

S.Joube, H. Grasland, D. Chamont, E.Brunet

View

Download (PDF)

Tags: Benchmarking, Computer science, Memory model, nVidia, nVidia Quadro RTX 5000, SYCL

March 26, 2023 by hgpu

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

Gregor Daiß, Patrick Diehl, Hartmut Kaiser, Dirk Pflüger

View

Download (PDF)

Source codes

Tags: AMD Radeon Instinct MI100, Astrophysics, Computer science, CUDA, HIP, nVidia, nVidia A100, Package, SYCL

March 19, 2023 by hgpu

Porting numerical integration codes from CUDA to oneAPI: a case study

Ioannis Sakiotis, Kamesh Arumugam, Marc Paterno, Desh Ranjan, Balsa Terzic, Mohammad Zubair

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, nVidia, nVidia V100, Package, SYCL

February 26, 2023 by hgpu

Optimization of massive data applications on heterogeneous architectures

José Carlos Romero Moreno

View

Download (PDF)

Source codes

Tags: Computer science, FPGA, Heterogeneous systems, Intel, Intel UHD 630, OpenCL, Package, SYCL, Thesis

February 5, 2023 by hgpu

Fast Merge Tree Computation via SYCL

Arnur Nigmetov, Dmitriy Morozov

View

Download (PDF)

Source codes

Tags: Computational Geometry, Computer science, nVidia, nVidia GeForce RTX 2080 Ti, OpenMP, Package, SYCL

January 29, 2023 by hgpu

Portable C++ Code that can Look and Feel Like Fortran Code with Yet Another Kernel Launcher (YAKL)

Matthew Norman, Isaac Lyngaas, Abhishek Bagusetty, Mark Berrill

View

Download (PDF)

Source codes

Tags: Computer science, Fortran, nVidia, Package, SYCL, Tesla V100

December 19, 2022 by hgpu

Towards energy efficiency and productivity for decision making in mobile robot navigation

Denisa-Andreea Constantinescu

View

Download (PDF)

Tags: Computer science, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson Nano, nVidia Jetson TX1, nVidia Jetson TX2, OpenCL, Robotics, SYCL

December 11, 2022 by hgpu

SkyFlow: Heterogeneous streaming for skyline computation using FlowGraph and SYCL

Jose Carlos Romero, Angeles Navarro, Andres Rodrıguez, Rafael Asenjo

View

Download (PDF)

Tags: Computer science, Heterogeneous systems, Intel, Intel UHD 630, OpenMP, SYCL

December 4, 2022 by hgpu

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

CONCUR: Benchmarking LLMs for Concurrent Code Generation

HIPRT: Ray Tracing using HIP

Ray Tracing using HIP

MXFP4 Training Support Codebase

Practical FP4 Training for Large-Scale MoE Models on Hopper GPUs

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

Fuzzing Loop Optimizations in Compilers for C++ and Data-Parallel Languages

Understanding Performance Portability of Bioinformatics Applications in SYCL on an NVIDIA GPU

Managing heterogeneous device memory using C++17 memory resources

Comparing SYCL data transfer strategies for tracking use cases

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

Porting numerical integration codes from CUDA to oneAPI: a case study

Optimization of massive data applications on heterogeneous architectures

Fast Merge Tree Computation via SYCL

Portable C++ Code that can Look and Feel Like Fortran Code with Yet Another Kernel Launcher (YAKL)

Towards energy efficiency and productivity for decision making in mobile robot navigation

SkyFlow: Heterogeneous streaming for skyline computation using FlowGraph and SYCL

Recent source codes

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

HIPRT: Ray Tracing using HIP

MXFP4 Training Support Codebase

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

Most viewed papers (last 30 days)