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Framework for Parallel Kernels Auto-tuning

Filip Petrovič

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Tags: Auto-Tuning, Computer science, CUDA, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 750, nVidia GeForce GTX 970, OpenCL, Package, Performance, Thesis

November 10, 2019 by hgpu

A Benchmark Set of Highly-efficient CUDA and OpenCL Kernels and its Dynamic Autotuning with Kernel Tuning Toolkit

Filip Petrovič, David Střelák, Jana Hozzová, Jaroslav Oľha, Richard Trembecký, Siegfried Benkner, Jiří Filipovič

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Tags: AMD Radeon RX Vega 56, Auto-Tuning, Benchmarking, Computer science, CUDA, Electron microscopy, Intel Xeon Phi, Microscopy, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 750, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Performance, performance portability, Tesla K20

October 27, 2019 by hgpu

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

Philippe Tillet, H. T. Kung, David Cox

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Tags: Compilers, Computer science, CUDA, Deep learning, High-level Languages, LLVM, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX 1070, Package

June 30, 2019 by hgpu

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

Grigory Glukhov, Aleksandra Soltan

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Tags: 3D Graphics and Realism, AMD RX Vega 64, ATI, Neural networks, nVidia, nVidia GeForce GTX 1070, nVidia GeForce RTX 2070, Thesis, Voxelization, Vulkan

June 23, 2019 by hgpu

Improving OpenCL Performance by Specializing Compiler Phase Selection and Ordering

Ricardo Nobre, Luis Reis, Joao M. P. Cardoso

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Tags: Computer science, nVidia, nVidia GeForce GTX 1070, OpenCL, Performance, PTX

October 28, 2018 by hgpu

pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment

Sven Warris, N. Roshan N. Timal, Marcel Kempenaar, Arne M. Poortinga, Henri van de Geest, Ana L. Varbanescu, Jan-Peter Nap

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 1070, OpenCL, Package, Python, Sequence alignment, Smith-Waterman algorithm

January 13, 2018 by hgpu

Large Integer Arithmetic in GPU for Cryptography

Lee Wen Dick

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1070, Security, Thesis

August 26, 2017 by hgpu

Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture

Xu Liu, Langshi Chen, Jesun S. Firoz, Judy Qiu, Lei Jiang

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Tags: Computer science, CUDA, Graph theory, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1070

August 17, 2017 by hgpu

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Learnergy: a Python library for energy-based machine learning models

Learnergy: Energy-based Machine Learners

Towards automated kernel selection in machine learning systems: A SYCL case study

Towards automated kernel selection in machine learning systems: A SYCL case study

CLFuzz

Automated test generation for OpenCL kernels using fuzzing and constraint solving

High-Performance Graph Primitives on GPUs

Fast Gunrock Subgraph Matching (GSM) on GPUs

Inline Vector Compression for Computational Physics

Inline Vector Compression for Computational Physics

AvA: Automatic virtualization of (general) accelerators

AvA: Accelerated Virtualization of Accelerators

GPGPU Verification of Radix Sort

Let’s sort this out: GPGPU Verification of Radix Sort

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2020

April

27-29

Munich, Germany

8th International Workshop on OpenCL, including SYCLCon, 2019

2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

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