high performance computing on graphics processing units: hgpu.org

Programming

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Deep Language Models for Software Testing and Optimisation

Foivos Tsimpourlas

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Tags: Benchmarking, Computer science, Deep learning, nVidia, nVidia GeForce GTX 1080, nVidia GeForce Titan X, OpenCL, Package, Software Engineering, Thesis

June 25, 2023 by hgpu

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Aurélien François Gilbert Bloch

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Tags: Compilers, Computer science, CUDA, Design space exploration, DSP, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 1660, nVidia GeForce RTX 3080 Ti, Package, Thesis

June 25, 2023 by hgpu

DGEMM on Integer Matrix Multiplication Unit

Hiroyuki Ootomo, Katsuhisa Ozaki, Rio Yokota

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Tags: Computer science, CUBLAS, CUDA, Deep learning, Linear Algebra, Machine learning, Matrix multiplication, nVidia, nVidia A100, nVidia Jetson AGX Orin, nVidia RTX 6000 Ada, nVidia Titan RTX, Package

June 25, 2023 by hgpu

GPU First – Execution of Legacy CPU Codes on GPUs

Shilei Tian, Tom Scogland, Barbara Chapman, Johannes Doerfert

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Tags: Benchmarking, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia A100, OpenMP

June 25, 2023 by hgpu

ACC Saturator: Automatic Kernel Optimization for Directive-Based GPU Code

Kazuaki Matsumura, Simon Garcia De Gonzalo, Antonio J. Peña

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Tags: Algorithms, Benchmarking, Code generation, Compilers, Computer science, nVidia, OpenACC, OpenMP, Tesla A100

June 25, 2023 by hgpu

Improving Performance of Iterative Applications through Interleaved Execution of Approximated CUDA Kernels

Gabriel Freytag

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Tags: Computer science, CUDA, Machine learning, Mixed precision, Neural networks, nVidia, nVidia A100, nVidia P100, Thesis

June 18, 2023 by hgpu

Reducing branch divergence to speed up parallel execution of unit testing on GPUs

Taghreed Bagies, Wei Le, Jeremy Sheafer, Ali Jannesari

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Tags: Benchmarking, Computer science, CUDA, nVidia, Package, Performance, Tesla V100

June 18, 2023 by hgpu

Efficient GPU implementation of a class of array permutations

Mathis Bouverot-Dupuis, Mary Sheeran

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Tags: Algorithms, AMD Radeon Instinct MI100, ATI, Computer science, CUDA, Haskell, nVidia, nVidia GeForce RTX 4090, Package

June 18, 2023 by hgpu

cuCatch: A Debugging Tool for Efficiently Catching Memory Safety Violations in CUDA Applications

Mohamed Tarek Ibn Ziad, Sana Damani, Aamer Jaleel, Stephen W. Keckler, Mark Stephenson

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce RTX 2080 Ti, OpenACC, OpenCL, Security

June 18, 2023 by hgpu

EfficientBioAI: Making Bioimaging AI Models Efficient in Energy, Latency and Representation

Yu Zhou, Justin Sonneck, Sweta Banerjee, Stefanie Dörr, Anika Grüneboom, Kristina Lorenz, Jianxu Chen

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Tags: Artificial intelligence, Biology, Computer science, CUDA, nVidia, nVidia Quadro RTX 4000, Package

June 18, 2023 by hgpu

Program Analysis and Machine Learning based Approach to Predict Power Consumption of CUDA Kernel

Gargi Alavani, Jineet Desai, Snehanshu Saha, Santonu Sarkar

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Tags: Benchmarking, Computer science, CUDA, Energy-efficient computing, Machine learning, nVidia, Package, Tesla K20, Tesla M60, Tesla V100

June 11, 2023 by hgpu

GPUHarbor: Testing GPU Memory Consistency at Large

Reese Levine, Mingun Cho, Devon McKee, Andrew Quinn, Tyler Sorensen

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Tags: AMD Radeon Pro 5500M, ATI, Computer science, Memory model, nVidia, nVidia GeForce RTX 3080, nVidia Tegra TX1, OpenCL, Performance

June 11, 2023 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

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

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

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high performance computing on graphics processing units: hgpu.org

Programming

Deep Language Models for Software Testing and Optimisation

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

DGEMM on Integer Matrix Multiplication Unit

GPU First – Execution of Legacy CPU Codes on GPUs

ACC Saturator: Automatic Kernel Optimization for Directive-Based GPU Code

Improving Performance of Iterative Applications through Interleaved Execution of Approximated CUDA Kernels

Reducing branch divergence to speed up parallel execution of unit testing on GPUs

Efficient GPU implementation of a class of array permutations

cuCatch: A Debugging Tool for Efficiently Catching Memory Safety Violations in CUDA Applications

EfficientBioAI: Making Bioimaging AI Models Efficient in Energy, Latency and Representation

Program Analysis and Machine Learning based Approach to Predict Power Consumption of CUDA Kernel

GPUHarbor: Testing GPU Memory Consistency at Large

Recent source codes

Code generated HPC Kernels Using Llama-2-70b

Scope is all you need: Transforming LLMs for HPC Code

pocl - Portable Computing Language

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

openCLDispatcher

CEED Benchmarks

Sieve: Stratified GPU-Compute Workload Sampling

EngineCL: Usability and Performance in Heterogeneous Computing

Ginkgo: high-performance linear algebra library for manycore systems

AlphaFold2

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