Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

GPUs and the Future of Parallel Computing

Published: 01 September 2011 Publication History

Abstract

This article discusses the capabilities of state-of-the art GPU-based high-throughput computing systems and considers the challenges to scaling single-chip parallel-computing systems, highlighting high-impact areas that the computing research community can address. Nvidia Research is investigating an architecture for a heterogeneous high-performance computing system that seeks to address these challenges.

Cited By

View all

Recommendations

Comments

Information & Contributors

Information

Published In

cover image IEEE Micro
IEEE Micro  Volume 31, Issue 5
September 2011
79 pages

Publisher

IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 September 2011

Author Tags

  1. GPU
  2. Parallel-computer architecture
  3. energy-efficient computing

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 01 Sep 2024

Other Metrics

Citations

Cited By

View all
  • (2024)ADS-CNNFuture Generation Computer Systems10.1016/j.future.2024.04.038158:C(138-149)Online publication date: 1-Sep-2024
  • (2024)The emergence of compositionality in a brain-inspired cognitive architectureCognitive Systems Research10.1016/j.cogsys.2024.10121586:COnline publication date: 1-Aug-2024
  • (2023)Extension VM: Interleaved Data Layout in Vector MemoryACM Transactions on Architecture and Code Optimization10.1145/363152821:1(1-23)Online publication date: 7-Nov-2023
  • (2023)Grape: Practical and Efficient Graphed Execution for Dynamic Deep Neural Networks on GPUsProceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture10.1145/3613424.3614248(1364-1380)Online publication date: 28-Oct-2023
  • (2023)Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow PostsProceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3611643.3616365(1444-1456)Online publication date: 30-Nov-2023
  • (2023)CoMeFa: Deploying Compute-in-Memory on FPGAs for Deep Learning AccelerationACM Transactions on Reconfigurable Technology and Systems10.1145/360350416:3(1-34)Online publication date: 27-Jul-2023
  • (2023)MESA: Microarchitecture Extensions for Spatial Architecture GenerationProceedings of the 50th Annual International Symposium on Computer Architecture10.1145/3579371.3589084(1-14)Online publication date: 17-Jun-2023
  • (2023)Enhanced regularization for on-chip training using analog and temporary memory weightsNeural Networks10.1016/j.neunet.2023.07.001165:C(1050-1057)Online publication date: 1-Aug-2023
  • (2023)H-Storm: A Hybrid CPU-FPGA Architecture to Accelerate Apache StormJournal of Grid Computing10.1007/s10723-023-09692-921:4Online publication date: 7-Nov-2023
  • (2023)TorchProbe: Fuzzing Dynamic Deep Learning CompilersProgramming Languages and Systems10.1007/978-981-99-8311-7_15(310-331)Online publication date: 26-Nov-2023
  • Show More Cited By

View Options

View options

Get Access

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media