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Assessing Opportunities of SYCL and Intel oneAPI for Biological Sequence Alignment

Manuel Costanzo, Enzo Rucci, Carlos García Sánchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: Bioinformatics, Biology, Computational biology, Computer science, CUDA, Heterogeneous systems, Intel, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, OpenCL, Sequence alignment, SYCL, Tesla V100

November 27, 2022 by hgpu

Training a Vision Transformer from scratch in less than 24 hours with 1 GPU

Saghar Irandoust, Thibaut Durand, Yunduz Rakhmangulova, Wenjie Zi, Hossein Hajimirsadeghi

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Tags: Benchmarking, Computer science, Computer vision, Deep learning

November 20, 2022 by hgpu

Hardware Checkpointing and Productive Debugging Flows for FPGAs

Sameh Attia

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Tags: Computer science, FPGA, Package, Thesis

November 20, 2022 by hgpu

Challenges and Techniques for Transparent Acceleration of Unmodified Big Data Applications

Maria Nektaria Xekalaki

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Tags: Benchmarking, Computer science, CUDA, FPGA, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX 1060, nVidia Quadro GP100, OpenCL, Package, Performance, Tesla V100, Thesis

November 20, 2022 by hgpu

Going green: optimizing GPUs for energy efficiency through model-steered auto-tuning

Richard Schoonhoven, Bram Veenboer, Ben van Werkhoven, Kees Joost Batenburg

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia RTX A4000, OpenCL, Package, Tesla A100

November 20, 2022 by hgpu

TorchOpt: An Efficient Library for Differentiable Optimization

Jie Ren, Xidong Feng, Bo Liu, Xuehai Pan, Yao Fu, Luo Mai, Yaodong Yang

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Tags: Computer science, CUDA, Deep learning, Mathematical Software, nVidia, OpenMP, Package, PyTorch

November 20, 2022 by hgpu

Capturing the Memory Topology of GPUs

Dominik Größler

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce 840 M, nVidia GeForce RTX 2080 Ti, nVidia Quadro P 6000, Package, Performance, PTX, Tesla K20, Tesla V100, Thesis

November 13, 2022 by hgpu

A Study on Neural-based Code Summarization in Low-resource Settings

Yang He

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Tags: Computer science, CUDA, Deep learning, nVidia, PyTorch, Software Engineering, Tesla V100, Thesis

November 13, 2022 by hgpu

iGniter: Interference-Aware GPU Resource Provisioning for Predictable DNN Inference in the Cloud

Fei Xu, Jianian Xu, Jiabin Chen, Li Chen, Ruitao Shang, Zhi Zhou, Fangming Liu

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Tags: Cloud, Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla V100

November 13, 2022 by hgpu

pyGSL: A Graph Structure Learning Toolkit

Max Wasserman, Gonzalo Mateos

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Tags: Computer science, Machine learning, Package, PyTorch, Signal processing

November 13, 2022 by hgpu

Using scheduling entropy amplification in CUDA/OpenMP code to exhibit non-reproducibility issues

David Defour

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Tags: Computer science, CUDA, Floating point error, nVidia, nVidia GeForce RTX 2060, OpenMP

November 6, 2022 by hgpu

An Open-source FPGA Library for Data Sorting

Ryohei Kobayashi, Kento Miura, Norihisa Fujita, Taisuke Boku, Toshiyuki Amagasa

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Tags: Algorithms, Computer science, FPGA, OpenCL, Package, Sorting

November 6, 2022 by hgpu

GPUODEBenchmarks: Comparsion of Julia's GPU Kernel based ODE solvers with other open-source GPU ODE solvers

Automating Heterogeneous Parallelism in Numerical Differential Equations

Dat3M: Memory Model Aware Verification

Towards Unified Analysis of GPU Consistency

NVIDIA Federated Learning Application Runtime Environment

Supercharging Federated Learning with Flower and NVIDIA FLARE

Chat AI: A Seamless Slurm-Native Solution for HPC-Based Services

PSCToolkit: solving sparse linear systems with a large number of GPUs

CATBench: Benchmarking Framework

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

General-purpose Polyhedral Compilers

A Survey of General-purpose Polyhedral Compilers

Optimal Kernel Orchestration for Tensor Programs with Korch

Astaroth: A Scalable Multi-GPU Library for Stencil Computations

Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. Empirical tricks for LLM Jailbreaking

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs

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high performance computing on graphics processing units: hgpu.org

Assessing Opportunities of SYCL and Intel oneAPI for Biological Sequence Alignment

Training a Vision Transformer from scratch in less than 24 hours with 1 GPU

Hardware Checkpointing and Productive Debugging Flows for FPGAs

Challenges and Techniques for Transparent Acceleration of Unmodified Big Data Applications

Going green: optimizing GPUs for energy efficiency through model-steered auto-tuning

TorchOpt: An Efficient Library for Differentiable Optimization

Capturing the Memory Topology of GPUs

A Study on Neural-based Code Summarization in Low-resource Settings

pyGSL: A Graph Structure Learning Toolkit

Using scheduling entropy amplification in CUDA/OpenMP code to exhibit non-reproducibility issues

An Open-source FPGA Library for Data Sorting

Recent source codes

GPUODEBenchmarks: Comparsion of Julia's GPU Kernel based ODE solvers with other open-source GPU ODE solvers

Dat3M: Memory Model Aware Verification

NVIDIA Federated Learning Application Runtime Environment

Chat AI: A Seamless Slurm-Native Solution for HPC-Based Services

PSCToolkit: solving sparse linear systems with a large number of GPUs

CATBench: Benchmarking Framework

General-purpose Polyhedral Compilers

Optimal Kernel Orchestration for Tensor Programs with Korch

Astaroth: A Scalable Multi-GPU Library for Stencil Computations

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. Empirical tricks for LLM Jailbreaking

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