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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

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Evaluation of Rust for GPGPU high performance computing

Evaluation of Rust for GPGPU high-performance computing

SCAMP: CPU/GPU Implementation of the SCAMP algorithm for computing the matrix profile

Optimization of massive data applications on heterogeneous architectures

A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Pulsar search acceleration using FPGAs and OpenCL templates

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

Fast Merge Tree Computation via SYCL

pocl: Portable Computing Language

Efficient OpenCL system integration of non-blocking FPGA accelerators

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

AutoDDL: Automatic Distributed Deep Learning with Asymptotically Optimal Communication

Python Suite for Advanced General Ensemble Simulations

PySAGES: flexible, advanced sampling methods accelerated with GPUs

GPU load-balancing library for regular and irregular computations

A Programming Model for GPU Load Balancing

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high performance computing on graphics processing units: hgpu.org

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

Evaluation of Rust for GPGPU high performance computing

SCAMP: CPU/GPU Implementation of the SCAMP algorithm for computing the matrix profile

A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code

FDAS: Fourier Domain Acceleration Search, FPGA-accelerated with OpenCL

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

Reeber: a library for shared- and distributed-memory parallel computation of merge trees

pocl: Portable Computing Language

OneFlow: a deep learning framework designed to be user-friendly, scalable and efficient

Python Suite for Advanced General Ensemble Simulations

GPU load-balancing library for regular and irregular computations

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