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Towards Alignment of Parallelism in SYCL and ISO C++

Simon John Pennycook, Ben Ashbaugh, James Brodman, Michael Kinsner, Steffen Larsen, Greg Lueck, Roland Schulz, Michael Voss

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Tags: Computer science, OpenCL, Performance, SYCL

May 14, 2023 by hgpu

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

Yanwen Xu, Ang Li, Tyler Sorensen

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

Towards Alignment of Parallelism in SYCL and ISO C++

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

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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