high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

Using Workload Characterization to Guide High Performance Graph Processing

Mohamed W. Hassan

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, nVidia, OpenCL, Optimization, Tesla K20, Thesis

May 30, 2021 by hgpu

cuSZ(x): Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs

Jiannan Tian, Sheng Di, Xiaodong Yu, Cody Rivera, Kai Zhao, Sian Jin, Yunhe Feng, Xin Liang, Dingwen Tao, Franck Cappello

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Tags: Algorithms, Compression, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Tesla A100, Tesla V100

May 30, 2021 by hgpu

PeriPy – A High Performance OpenCL Peridynamics Package

B. Boys, T. J. Dodwell, M. Hobbs, M. Girolami

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Tags: Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Python

May 16, 2021 by hgpu

Sylkan: Towards a Vulkan Compute Target Platform for SYCL

Peter Thoman, Daniel Gogl, Thomas Fahringer

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Tags: Benchmarking, Computer science, Data parallelism, Heterogeneous systems, OpenCL, SYCL, Video, Vulkan

May 9, 2021 by hgpu

Irregularity Mitigation and Portability Abstractions for Accelerated Sparse Matrix Factorization

Daniel Thürck

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Tags: Algorithms, Computer science, Factorization, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan V, OpenCL, Sparse matrix, Thesis

May 9, 2021 by hgpu

Ripple: Simplified Large-Scale Computation on Heterogeneous Architectures with Polymorphic Data Layout

Robert Clucas, Philip Blakely, Nikolaos Nikiforakis

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Tesla V100

April 25, 2021 by hgpu

Multiple-Tasks on Multiple-Devices (MTMD): Exploiting Concurrency in Heterogeneous Managed Runtimes

Michail Papadimitriou, Eleni Markou, Juan Fumero, Athanasios Stratikopoulos, Florin Blanaru, Christos Kotselidis

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Tags: Computer science, Heterogeneous systems, Java, Machine learning, nVidia, nVidia GeForce GTX 1650, OpenCL

April 11, 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

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

Xinxin Mei, Qiang Wang, Xiaowen Chu, Hai Liu, Yiu-Wing Leung, Zongpeng Li

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Tags: Computer science, Deep learning, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia GeForce GTX 1080 Ti, Package, Task scheduling

April 5, 2021 by hgpu

Integrating Accelerators in Heterogeneous Systems

Ján Veselý

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Python, Thesis

March 7, 2021 by hgpu

Acceleration of Intrusion Detection in Encrypted Network Traffic Using Heterogeneous Hardware

Eva Papadogiannaki, Sotiris Ioannidis

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Tags: Computer science, Filtering, Heterogeneous systems, Intel UHD 630, nVidia, nVidia GeForce GTX 980, OpenCL, Security

February 28, 2021 by hgpu

Optimal program variant generation for hybrid manycore systems

Cristian Urlea

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Tags: Computer science, Design space exploration, FPGA, Heterogeneous systems, OpenCL, performance portability, Thesis

February 21, 2021 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

Using Workload Characterization to Guide High Performance Graph Processing

cuSZ(x): Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs

PeriPy – A High Performance OpenCL Peridynamics Package

Sylkan: Towards a Vulkan Compute Target Platform for SYCL

Irregularity Mitigation and Portability Abstractions for Accelerated Sparse Matrix Factorization

Ripple: Simplified Large-Scale Computation on Heterogeneous Architectures with Polymorphic Data Layout

Multiple-Tasks on Multiple-Devices (MTMD): Exploiting Concurrency in Heterogeneous Managed Runtimes

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

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

Integrating Accelerators in Heterogeneous Systems

Acceleration of Intrusion Detection in Encrypted Network Traffic Using Heterogeneous Hardware

Optimal program variant generation for hybrid manycore systems

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

Most viewed papers (last 30 days)