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Tensor Computation Based on Heterogeneous Memory

Jiawen Liu

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Tags: Computer science, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Prefetch, Thesis

July 3, 2022 by hgpu

An experimental study of group-by and aggregation on CPU-GPU processors

Hua Luan, Lei Chang

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Tags: Computer science, Databases, Hashing, OpenCL

June 26, 2022 by hgpu

Securing GPU via Region-based Bounds Checking

Jaewon Lee, Yonghae Kim, Jiashen Cao, Euna Kim, Jaekyu Lee, Hyesoon Kim

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce RTX 2080, OpenCL, Security

June 19, 2022 by hgpu

On the Compilation Performance of Current SYCL Implementations

Peter Thoman, Facundo Molina Heredia, Thomas Fahringer

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Tags: Code generation, Compilers, Computer science, Heterogeneous systems, OpenCL, Package, Performance, SYCL

June 12, 2022 by hgpu

User’s needs influencing HPC technologies

E. Athanasaki, N. Meyer, M. Cestari, A.Tuncer Durak, A. Tekin, P. Gschwandtner

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Tags: AI, Artificial intelligence, Cloud, Computer science, CUDA, HIP, HPC, nVidia, OpenCL, Security, SYCL

May 29, 2022 by hgpu

GPU Ray Tracing with Monte Carlo Methods

Daniele Alma

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Tags: 3D Graphics and Realism, Algorithms, nVidia, nVidia GeForce GTX 930 MX, OpenCL, Raytracing, Rendering, Thesis

May 22, 2022 by hgpu

AnySeq/GPU: A Novel Approach for Faster Sequence Alignment on GPUs

André Müller, Bertil Schmidt, Richard Membarth, Roland Leißa, Sebastian Hack

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Tags: AMD Radeon Instinct MI100, ATI, Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, nVidia GeForce RTX 3090, OpenCL, Package, Sequence alignment, Tesla A100

May 22, 2022 by hgpu

Can We Run in Parallel? Automating Loop Parallelization for TornadoVM

Rishi Sharma, Shreyansh Kulshreshtha, Manas Thakur

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Tags: Computer science, FPGA, Heterogeneous systems, Java, OpenCL

May 15, 2022 by hgpu

Experience of Migrating a Parallel Graph Coloring Program from CUDA to SYCL

Zheming Jin

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Tags: Benchmarking, Computer science, CUDA, Graph theory, nVidia, OpenCL, Package, Performance, SYCL

May 8, 2022 by hgpu

Analytical Performance Estimation during Code Generation on Modern GPUs

Dominik Ernst, Markus Holzer, Georg Hager, Matthias Knorr, Gerhard Wellein

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Tags: Code generation, Computer science, CUDA, Lattice Boltzmann model, Machine learning, nVidia, OpenCL, Package, Tesla A100, Tesla V100

May 8, 2022 by hgpu

End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning

Yao Xiao, Guixiang Ma, Nesreen K. Ahmed, Mihai Capota, Theodore Willke, Shahin Nazarian, Paul Bogdan

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Tags: Computer science, Heterogeneous systems, Machine learning, Neural networks, OpenCL

May 1, 2022 by hgpu

Improving performance of SYCL applications on CPU architectures using LLVM-directed compilation flow

Pietro Ghiglio, Uwe Dolinsky, Mehdi Goli, Kumudha Narasimhan

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Tags: Computer science, CUDA, nVidia, OpenCL, Performance, performance portability, SYCL

May 1, 2022 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

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high performance computing on graphics processing units: hgpu.org

Tensor Computation Based on Heterogeneous Memory

An experimental study of group-by and aggregation on CPU-GPU processors

Securing GPU via Region-based Bounds Checking

On the Compilation Performance of Current SYCL Implementations

GPU Ray Tracing with Monte Carlo Methods

AnySeq/GPU: A Novel Approach for Faster Sequence Alignment on GPUs

Can We Run in Parallel? Automating Loop Parallelization for TornadoVM

Experience of Migrating a Parallel Graph Coloring Program from CUDA to SYCL

Analytical Performance Estimation during Code Generation on Modern GPUs

End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning

Improving performance of SYCL applications on CPU architectures using LLVM-directed compilation flow

Recent source codes

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

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