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Guardian: Safe GPU Sharing in Multi-Tenant Environments

Manos Pavlidakis, Giorgos Vasiliadis, Anargyros Argyros, Stelios Mavridis, Antony Chazapis, Angelos Bilas

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Tags: Computer science, CUDA, nVidia, nVidia GeForce RTX 3080 Ti, nVidia RTX A4000, PTX, Security

December 8, 2024 by hgpu

An End-to-End Programming Model for AI Engine Architectures

Maksim Levental

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Tags: Artificial intelligence, Computer science, Deep learning, nVidia, nVidia GeForce RTX 3080 Ti, Thesis, Vulkan

June 23, 2024 by hgpu

An Evaluation of Directive-Based Parallelization on the GPU Using a Parboil Benchmark

Jovan Ðukic, Marko Mišic

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce RTX 3080 Ti, OpenACC, OpenCL, OpenMP

November 12, 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

Dataloader Parameter Tuner: An Automated Dataloader Parameter Tuner for Deep Learning Models

JooYoung Park, DoangJoo Synn, XinYu Piao, Jong-Kook Kim

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce RTX 3080 Ti, Performance, Prefetch

October 16, 2022 by hgpu

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

Farui Wang, Weizhe Zhang, Shichao Lai, Meng Hao, Zheng Wang

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Tags: Benchmarking, Computer science, CUDA, Energy-efficient computing, Machine learning, nVidia, nVidia GeForce RTX 3080 Ti, Package

January 9, 2022 by hgpu

GPU-accelerated Faster Mean Shift with euclidean distance metrics

Le You, Han Jiang, Jinyong Hu, Chorng Chang, Lingxi Chen, Xintong Cui, Mengyang Zhao

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Tags: Algorithms, Clustering, CUDA, Image processing, nVidia, nVidia GeForce RTX 3070, nVidia GeForce RTX 3080 Ti, nVidia Quadro P 5000, Package, Pattern recognition, Tesla P100

January 2, 2022 by hgpu

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

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high performance computing on graphics processing units: hgpu.org

Guardian: Safe GPU Sharing in Multi-Tenant Environments

An End-to-End Programming Model for AI Engine Architectures

An Evaluation of Directive-Based Parallelization on the GPU Using a Parboil Benchmark

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

Dataloader Parameter Tuner: An Automated Dataloader Parameter Tuner for Deep Learning Models

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

GPU-accelerated Faster Mean Shift with euclidean distance metrics

Recent source codes

XaaS containers

microSYCL: SYCL micro-benchmarks repository

SYCL Container

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

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