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Embracing Heterogeneity in Modern GPUs

Tang, Xulong (2021) Embracing Heterogeneity in Modern GPUs. In: Pitt Momentum Fund 2021.

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Abstract

Graphics Processing Units is one of the most widely adopted parallel computing engines for modern applications. However, due to the “memory wall”, the scaling of GPUs is lagging behind the ever-growing complexity of application algorithms and ever-increasing data volume of inputs. Near-data computing (NDC) is a widely-acknowledged computing paradigm that alleviates the memory wall problem by offloading computation to data instead of conventional fetching data to computation. While the NDC GPU architectures have been proposed and studied, there are several key questions that remain unanswered: i) what portions of an application's execution should be launched as GPU device kernels that can benefit from the executions on NDC GPU cores? ii) How to schedule these device kernels while considering the data reuse and sharing among them? iii) Where to execute these kernels if there are multiple potential candidate cores?


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Details

Item Type: Conference or Workshop Item (Poster)
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Tang, XulongTAX6@pitt.eduTAX60000-0002-3385-2053
Centers: Other Centers, Institutes, Offices, or Units > Office of Sponsored Research > Pitt Momentum Fund
Date: 2021
Event Title: Pitt Momentum Fund 2021
Event Type: Other
DOI or Unique Handle: 10.18117/twbx-ar46
Schools and Programs: School of Computing and Information > Computer Science
Refereed: No
Date Deposited: 26 Mar 2021 19:10
Last Modified: 26 Mar 2021 19:10
URI: http://d-scholarship.pitt.edu/id/eprint/40349

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