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Automated Generation of OpenCL Programs Based on Algebra-Algorithmic Approach

Anatoliy Doroshenko, Oleksii Beketov, Mykola Bondarenko, Olena Yatsenko

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 840 M, OpenCL

June 30, 2019 by hgpu

WCCV: Improving the Vectorization of IF-statements with Warp-Coherent Conditions

Huihui Sun, Florian Fey, Jie Zhao, Sergei Gorlatch

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Tags: Benchmarking, Code generation, Computer science, LLVM, OpenCL, Package, Performance

June 30, 2019 by hgpu

ReSYCLator: Transforming CUDA C++ source code into SYCL

Tobias Stauber, Peter Sommerlad

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, OpenCL, SYCL

June 27, 2019 by hgpu

Data-Parallel Flattening by Expansion

Martin Elsman, Troels Henriksen, Niels Gustav Westphal Serup

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Tags: Code generation, Computer science, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package

June 23, 2019 by hgpu

MGPUSim: Enabling Multi-GPU Performance Modeling and Optimization

Yifan Sun, Trinayan Baruah, Saiful A. Mojumder, Shi Dong, Xiang Gong, Shane Treadway, Yuhui Bao, Spencer Hance, Carter McCardwell, Vincent Zhao, Harrison Barclay, Amir Kavyan Ziabari, Zhongliang Chen, Rafael Ubal, Jose L. Abellan, John Kim, Ajay Joshi

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Tags: AMD R9 Nano, ATI, Computer science, Hardware Architecture, OpenCL, Package, Performance

June 23, 2019 by hgpu

High-Performance Deep Learning via a Single Building Block

Evangelos Georganas, Kunal Banerjee, Dhiraj Kalamkar, Sasikanth Avancha, Anand Venkat, Michael Anderson, Greg Henry, Hans Pabst, Alexander Heinecke

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Tags: Computer science, Deep learning, LSTM, Machine learning, Neural networks, OpenCL, Performance

June 20, 2019 by hgpu

Performance Evaluation and Analysis of Sparse Matrix and Graph Kernels on Heterogeneous Processors

Feng Zhang, Weifeng Liu, Ningxuan Feng, Jidong Zhai, Xiaoyong Du

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Tags: ATI, Computer science, Heterogeneous systems, OpenCL, Sparse matrix

June 16, 2019 by hgpu

SYCL Code Generation for Multigrid Methods

Stefan Groth, Christian Schmitt, Jürgen Teich, and Frank Hannig

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Tags: Code generation, Computer science, Differential equations, OpenCL, Package, Partial differential equations, PDEs

June 16, 2019 by hgpu

Performance Analysis and Automatic Tuning of Hash Aggregation on GPUs

Viktor Rosenfeld, Sebastian Bress, Steffen Zeuch, Tilmann Rabl, Volker Markl

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Tags: Algorithms, AMD Radeon R9 Fury, ATI, Computer science, Hashing, nVidia, nVidia GeForce GXT 1080, nVidia GeForce GXT 980, OpenCL, Performance, Tesla K40, Tesla V100

June 16, 2019 by hgpu

Temporospatial Epidemic Simulations Using Heterogeneous Computing

Dhananjai M. Rao

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Tags: Earth and Space Sciences, HPC, OpenCL, Package

June 9, 2019 by hgpu

PPOpenCL: a performance-portable OpenCL compiler with host and kernel thread code fusion

Ying Liu, Lei Huang, Mingchuan Wu, Huimin Cui, Fang Lv, Xiaobing Feng, Jingling Xue

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Tags: Code generation, Compilers, Computer science, OpenCL

June 9, 2019 by hgpu

LAMDA: Learning-Assisted Multi-Stage Autotuning for FPGA Design Closure

Ecenur Ustun, Shaojie Xiang, Jinny Gui, Cunxi Yu, Zhiru Zhang

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Tags: Computer science, FPGA, OpenCL, Performance

June 9, 2019 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP-AMD: Extending CUDA to AMD Platforms

Kernel Tuner

Testing and Mutation Testing for GPU Kernels

GT4Py: GridTools for Python

GT4Py: High Performance Stencils for Weather and Climate Applications using Python

miniBUDE: A BUDE virtual-screening benchmark, in many programming models

Evaluation of FPGA-based high performance computing platforms

gossip: Efficient Communication Primitives for Multi-GPU Systems

Accelerating bioinformatics applications on CUDA-enabled multi-GPU systems

AUCMEDI: a framework for Automated Classification of Medical Images

Frameworks in Medical Image Analysis with Deep Neural Networks

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

AFOCL: Portable OpenCL Programming of FPGAs via Automated Built-in Kernel Management

AFOCL: Portable OpenCL Programming of FPGAs via Automated Built-in Kernel Management

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

pp-template: Template for Performance-Portable code development, targeting HOST-DEVICE computer architectures

An approach to performance portability through generic programming

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