high performance computing on graphics processing units: hgpu.org

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Query Processing on Tensor Computation Runtimes

Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi

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Tags: Benchmarking, Cloud, Computer science, CUDA, Databases, Machine learning, nVidia, Package, Tesla P100

March 6, 2022 by hgpu

TCUDB: Accelerating Database with Tensor Processors

Yu-Ching Hu, Yuliang Li, Hung-Wei Tseng

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Tags: Computer science, CUDA, Databases, Machine learning, Matrix multiplication, Neural networks, nVidia, nVidia GeForce RTX 3090

December 19, 2021 by hgpu

Accelerating AutoDock VINA with GPUs

Shidi Tang, Ruiqi Chen, Mengru Lin, Qingde Lin, Yanxiang Zhu, Jiansheng Wu, Haifeng Hu, Ming Ling

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Tags: Chemistry, Databases, Heterogeneous systems, molecular docking, nVidia, nVidia GeForce GTX 1060, nVidia GeForce RTX 2080 Ti, nVidia GeForce RTX 3090, OpenCL, Package

October 17, 2021 by hgpu

The Art of Balance: A RateupDB Experience of Building a CPU/GPU Hybrid Database Product

Rubao Lee, Minghong Zhou, Chi Li, Shenggang Hu, Jianping Teng, Dongyang Li, Xiaodong Zhang

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia Quadro RTX 8000

August 29, 2021 by hgpu

TENSILE: A Tensor granularity dynamic GPU memory scheduler method towards multiple dynamic workloads system

Kaixin Zhang, Hongzhi Wang, Tongxin Li, Han Hu, Jiye Qiu, Songling Zou

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Tags: Computer science, CUDA, Databases, Deep learning, Machine learning, nVidia, nVidia GeForce RTX 2080 Ti, Task scheduling

May 30, 2021 by hgpu

An Investigation of Atomic Synchronization for Sort-Based Group-By Aggregation on GPUs

Bala Gurumurthy, David Broneske, Martin Schaler, Thilo Pionteck, Gunter Saake

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Tags: Computer science, Databases, Hashing, Heterogeneous systems, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce RTX 2080 Ti, OpenCL, Sorting

April 5, 2021 by hgpu

LS-CAT: A Large-Scale CUDA AutoTuning Dataset

Lars Bjertnes, Jacob O. Tørring, Anne C. Elster

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Tags: Benchmarking, Computer science, CUDA, Databases, Linear Algebra, Machine learning, nVidia, nVidia GeForce GTX 980, Tesla T4

April 5, 2021 by hgpu

Learning Massive Graph Embeddings on a Single Machine

Jason Mohoney, Roger Waleffe, Yiheng Xu, Theodoros Rekatsinas, Shivaram Venkataraman

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Tags: Computer science, CUDA, Databases, Graph theory, Machine learning, nVidia, Tesla V100

January 24, 2021 by hgpu

Hash-Based Authentication Revisited in the Age of High-Performance Computers

Niclas Hedam, Jakob Mollerup, Pinar Tozun

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Tags: Computer science, CUDA, Databases, Hashing, nVidia, nVidia GeForce RTX 2070, OpenCL, Security, Tesla V100

September 6, 2020 by hgpu

Open Source Face Recognition API

Diogo Neto Coxinho Mourisco da Conceição

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Tags: Algorithms, Computer science, Computer vision, Databases, Face detection, Package, Python, Thesis

April 12, 2020 by hgpu

LUDA: Boost LSM Key Value Store Compactions with GPUs

Peng Xu, Jiguang Wan, Ping Huang, Xiaogang Yang, Chenlei Tang, Fei Wu, Changsheng Xie

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 1080 Ti

April 12, 2020 by hgpu

GPU-accelerated dynamic programming for join-order optimization

Andreas Meister, Gunter Saake

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Tags: Computer science, Databases, nVidia, OpenCL, Tesla K20

February 2, 2020 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

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high performance computing on graphics processing units: hgpu.org

TCUDB: Accelerating Database with Tensor Processors

Accelerating AutoDock VINA with GPUs

The Art of Balance: A RateupDB Experience of Building a CPU/GPU Hybrid Database Product

TENSILE: A Tensor granularity dynamic GPU memory scheduler method towards multiple dynamic workloads system

An Investigation of Atomic Synchronization for Sort-Based Group-By Aggregation on GPUs

LS-CAT: A Large-Scale CUDA AutoTuning Dataset

Learning Massive Graph Embeddings on a Single Machine

Hash-Based Authentication Revisited in the Age of High-Performance Computers

Open Source Face Recognition API

LUDA: Boost LSM Key Value Store Compactions with GPUs

GPU-accelerated dynamic programming for join-order optimization

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

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