research-article

GPUs and the Future of Parallel Computing

Authors:

David GlascoAuthors Info & Claims

IEEE Micro, Volume 31, Issue 5

Pages 7 - 17

https://doi.org/10.1109/MM.2011.89

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.

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Byun HGupta USeo JDev KYoo JMeinerzhagen P(2024)3D IC Architecture Evaluation and Optimization with Digital Compute-in-Memory DesignsProceedings of the 29th ACM/IEEE International Symposium on Low Power Electronics and Design10.1145/3665314.3670838(1-6)Online publication date: 5-Aug-2024
https://dl.acm.org/doi/10.1145/3665314.3670838
Wan YXie XChen JXie KYi DLu YGai K(2024)ADS-CNNFuture Generation Computer Systems10.1016/j.future.2024.04.038158:C(138-149)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.future.2024.04.038
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Published In

IEEE Micro Volume 31, Issue 5

September 2011

79 pages

ISSN:0272-1732

Issue’s Table of Contents

Publisher

IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 September 2011

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Byun HGupta USeo JDev KYoo JMeinerzhagen P(2024)3D IC Architecture Evaluation and Optimization with Digital Compute-in-Memory DesignsProceedings of the 29th ACM/IEEE International Symposium on Low Power Electronics and Design10.1145/3665314.3670838(1-6)Online publication date: 5-Aug-2024
https://dl.acm.org/doi/10.1145/3665314.3670838
Wan YXie XChen JXie KYi DLu YGai K(2024)ADS-CNNFuture Generation Computer Systems10.1016/j.future.2024.04.038158:C(138-149)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.future.2024.04.038
Schneider H(2024)The emergence of compositionality in a brain-inspired cognitive architectureCognitive Systems Research10.1016/j.cogsys.2024.10121586:COnline publication date: 18-Jul-2024
https://dl.acm.org/doi/10.1016/j.cogsys.2024.101215
Zhang DLang QWang RShen L(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
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Zheng BYu CWang JDing YLiu YWang YPekhimenko G(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
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Yang WZhang CPan MChandra SBlincoe KTonella P(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
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Arora ABhamburkar ABorda AAnand TSehgal RHanindhito BGaillardon PKulkarni JJohn L(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
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Wang DLou JJin NMascarenhas EMahapatra RKinzer SGhodrati SYazdanbakhsh AEsmaeilzadeh HKim NSolihin YHeinrich M(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
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Singhal RSaraswat VDeshmukh SSubramoney SSomappa LBaghini MGanguly U(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
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On the Efficacy of a Fused CPU+GPU Processor (or APU) for Parallel Computing

Performance Tuning of Matrix Multiplication in OpenCL on Different GPUs and CPUs

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