skip to main content
10.1145/3366428acmconferencesBook PagePublication PagesgpgpuConference Proceedingsconference-collections
GPGPU '20: Proceedings of the 13th Annual Workshop on General Purpose Processing using Graphics Processing Unit
ACM2020 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
PPoPP '20: 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming San Diego California 23 February 2020
ISBN:
978-1-4503-7025-7
Published:
23 February 2020
Sponsors:
Recommend ACM DL
ALREADY A SUBSCRIBER?SIGN IN

Reflects downloads up to 13 Feb 2025Bibliometrics
Abstract

No abstract available.

Skip Table Of Content Section
research-article
Public Access
The Minos Computing Library: efficient parallel programming for extremely heterogeneous systems

Hardware specialization has become the silver bullet to achieve efficient high performance, from Systems-on-Chip systems, where hardware specialization can be "extreme", to large-scale HPC systems. As the complexity of the systems increases, so does the ...

research-article
Unveiling kernel concurrency in multiresolution filters on GPUs with an image processing DSL

Multiresolution filters, analyzing information at different scales, are crucial for many applications in digital image processing. The different space and time complexity at distinct scales in the unique pyramidal structure poses a challenge as well as ...

research-article
High-level hardware feature extraction for GPU performance prediction of stencils

High-level functional programming abstractions have started to show promising results for HPC (High-Performance Computing). Approaches such as Lift, Futhark or Delite have shown that it is possible to have both, high-level abstractions and performance, ...

research-article
GPGPU performance estimation for frequency scaling using cross-benchmarking

Dynamic Voltage and Frequency Scaling (D VFS) on General-Purpose Graphics Processing Units (GPGPUs) is now becoming one of the most significant techniques to balance computational performance and energy consumption. However, there are still few fast and ...

research-article
Automatic generation of specialized direct convolutions for mobile GPUs

Convolutional Neural Networks (CNNs) are a powerful and versatile tool for performing computer vision tasks in both resource constrained settings and server-side applications. Most GPU hardware vendors provide highly tuned libraries for CNNs such as ...

research-article
Custom code generation for a graph DSL

We present challenges faced in making a domain-specific language (DSL) for graph algorithms adapt to varying requirements of generating a spectrum of efficient parallel codes. Graph algorithms are at the heart of several applications, and achieving high ...

research-article
Automated test generation for OpenCL kernels using fuzzing and constraint solving

Graphics Processing Units (GPUs) are massively parallel processors offering performance acceleration and energy efficiency unmatched by current processors (CPUs) in computers. These advantages along with recent advances in the programmability of GPUs ...

Contributors
  • University of Virginia
  • Advanced Micro Devices, Inc.
  • Arm Limited

Index Terms

  1. Proceedings of the 13th Annual Workshop on General Purpose Processing using Graphics Processing Unit
          Index terms have been assigned to the content through auto-classification.

          Recommendations

          Acceptance Rates

          GPGPU '20 Paper Acceptance Rate 7 of 12 submissions, 58%;
          Overall Acceptance Rate 57 of 129 submissions, 44%
          YearSubmittedAcceptedRate
          GPGPU '2012758%
          GPGPU '1915640%
          GPGPU-1015853%
          GPGPU '1623939%
          GPGPU-7271244%
          GPGPU-6371541%
          Overall1295744%