high performance computing on graphics processing units: hgpu.org

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COOK Access Control on an embedded Volta GPU

Benjamin Lesage, Frédéric Boniol, Claire Pagetti

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia Jetson AGX Xavier

June 23, 2024 by hgpu

Memory Interference and Performance Prediction in GPU-Accelerated Heterogeneous Systems

Alessio Masola

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce RTX 2070, nVidia GeForce RTX 2080, nVidia Jetson AGX Xavier, Rendering, Thesis, Visualization

June 9, 2024 by hgpu

Software Optimization and Orchestration for Heterogeneous and Distributed Architectures

Francesco Lumpp

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson TX2, Performance, Thesis

April 21, 2024 by hgpu

Compiler-centric across-stack deep learning acceleration

Perry Gibson

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Tags: Compilers, Computer science, Deep learning, Design space exploration, nVidia, nVidia Jetson AGX Xavier, nVidia Titan RTX, Thesis

December 10, 2023 by hgpu

Performance/power assessment of CNN packages on embedded automotive platforms

Paolo Burgio, Gianluca Brilli

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Tags: CNN, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson Nano, nVidia Jetson TX2, Performance

October 22, 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

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

Real-Time High-Performance Computing for Embedded Control Systems

Alejandro Josué Calderón Torres

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Tags: Code generation, Computer science, Embedded high-performance computing, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson Nano, nVidia Jetson TX2, OpenCL, Tesla T4, Tesla V100, Thesis

August 7, 2022 by hgpu

FC_ACCEL: Enabling Efficient, Low-Latency and Flexible Inference in DNN Fully Connected Layers, using Optimized Checkerboard Block matrix decomposition, fast scheduling, and a resource efficient 1D PE array with a custom HBM2 memory subsystem

Nick Iliev, Amit R Trivedi

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Tags: CNN, Computer science, Deep learning, FPGA, Matrix decomposition, Neural networks, nVidia, nVidia Jetson AGX Xavier, Performance

February 13, 2022 by hgpu

Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs

Hamid Tabani, Fabio Mazzocchetti, Pedro Benedicte, Jaume Abella, Francisco J. Cazorla

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson TX2, Performance

April 25, 2021 by hgpu

Using Parallel Programming Models for Automotive Workloads on Heterogeneous Systems – a Case Study

Lukas Sommer, Florian Stock, Leonardo Solis-Vasquez, Andreas Koch

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Tags: Automotive, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson TX2, OpenCL, OpenMP

January 26, 2020 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

COOK Access Control on an embedded Volta GPU

Memory Interference and Performance Prediction in GPU-Accelerated Heterogeneous Systems

Software Optimization and Orchestration for Heterogeneous and Distributed Architectures

Compiler-centric across-stack deep learning acceleration

Performance/power assessment of CNN packages on embedded automotive platforms

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

Towards energy efficiency and productivity for decision making in mobile robot navigation

Real-Time High-Performance Computing for Embedded Control Systems

FC_ACCEL: Enabling Efficient, Low-Latency and Flexible Inference in DNN Fully Connected Layers, using Optimized Checkerboard Block matrix decomposition, fast scheduling, and a resource efficient 1D PE array with a custom HBM2 memory subsystem

Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs

Using Parallel Programming Models for Automotive Workloads on Heterogeneous Systems – a Case Study

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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