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The Impact of Modern Consumer GPUs on Commonly Used Secure Password Standards

Hani Khader

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Tags: AMD Radeon RX 6800, ATI, Computer science, CUDA, nVidia, nVidia GeForce RTX 4090, OpenCL, Security, Thesis

July 14, 2024 by hgpu

Harnessing Integrated CPU-GPU System Memory for HPC: a first look into Grace Hopper

Gabin Schieffer, Jacob Wahlgren, Jie Ren, Jennifer Faj, Ivy Peng

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Tags: Computer science, CUDA, HPC, Memory, nVidia, nVidia H100, Performance, Quantum computing

July 14, 2024 by hgpu

Automating Heterogeneous Parallelism in Numerical Differential Equations

Utkarsh

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Tags: AMD RX Vega 64, ATI, Computer science, CUDA, Differential equations, Factorization, Heterogeneous systems, Intel, Intel Arc A770, Julia, Numerical Analysis, nVidia, nVidia Quadro RTX 5000, Package, Tesla V100, Thesis

July 14, 2024 by hgpu

Automated C/C++ Program Repair for High-Level Synthesis via Large Language Models

Kangwei Xu, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Ulf Schlichtmann, Bing Li

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Tags: Code generation, Computer science, FPGA, HLS, LLM

July 14, 2024 by hgpu

Supercharging Federated Learning with Flower and NVIDIA FLARE

Holger R. Roth, Daniel J. Beutel, Yan Cheng, Javier Fernandez Marques, Heng Pan, Chester Chen, Zhihong Zhang, Yuhong Wen, Sean Yang, Isaac (Te-Chung)Yang, Yuan-Ting Hsieh, Ziyue Xu, Daguang Xu, Nicholas D. Lane, Andrew Feng

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Tags: AI, Algorithms, Computer science, nVidia, Package, Security

July 7, 2024 by hgpu

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

Ali Doosthosseini, Jonathan Decker, Hendrik Nolte, Julian M. Kunkel

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Tags: AI, Cloud, Computer science, HPC, LLM, nVidia, nVidia H100, Package, PC cluster

July 7, 2024 by hgpu

Towards Unified Analysis of GPU Consistency

Haining Tong, Natalia Gavrilenko, Hernán Ponce de León, Keijo Heljanko

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Tags: Computer science, Memory, nVidia, OpenCL, Package, PTX, Vulkan

July 7, 2024 by hgpu

Automatic Code Rewriting for Performance Portability

Alister Johnson

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Tags: Compilers, Computer science, HIP, OpenCL, OpenMP, performance portability, SYCL, Thesis

July 7, 2024 by hgpu

Composing Distributed Computations Through Task and Kernel Fusion

Rohan Yadav, Shiv Sundram, Wonchan Lee, Michael Garland, Michael Bauer, Alex Aiken, Fredrik Kjolstad

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Tags: Computer science, CUDA, Distributed computing, MPI, nVidia, nVidia DGX-A100, Python

June 30, 2024 by hgpu

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

Jacob O. Tørring, Carl Hvarfner, Luigi Nardi, Magnus Själander

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Tags: Benchmarking, Compilers, Computer science, Machine learning, nVidia, nVidia GeForce GTX Titan V, nVidia Titan RTX, OpenCL, Package

June 30, 2024 by hgpu

Adapting database components to heterogeneous environments

Dimitrios Koutsoukos

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Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia P100, Thesis

June 30, 2024 by hgpu

A Survey of General-purpose Polyhedral Compilers

Arun Thangamani, Vincent Loechner, Stéphane Genaud

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia A100, OpenCL, Package, survey

June 30, 2024 by hgpu

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

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high performance computing on graphics processing units: hgpu.org

The Impact of Modern Consumer GPUs on Commonly Used Secure Password Standards

Harnessing Integrated CPU-GPU System Memory for HPC: a first look into Grace Hopper

Automating Heterogeneous Parallelism in Numerical Differential Equations

Automated C/C++ Program Repair for High-Level Synthesis via Large Language Models

Supercharging Federated Learning with Flower and NVIDIA FLARE

Towards Unified Analysis of GPU Consistency

Automatic Code Rewriting for Performance Portability

Composing Distributed Computations Through Task and Kernel Fusion

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

Adapting database components to heterogeneous environments

A Survey of General-purpose Polyhedral Compilers

Recent source codes

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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