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Title:Automating heterogeneous memory management
Author(s):Brooks, Alex
Director of Research:Snir, Marc
Doctoral Committee Chair(s):Snir, Marc
Doctoral Committee Member(s):Olson, Luke N; Garzaran, Maria; Scogland, Thomas R. W.
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):heterogeneous
memory
system
automated
analysis
profiling
framework
access
patterns
latency
bandwidth
Abstract:Hardware heterogeneity is becoming an increasingly common feature in high-performance computing systems. Unfortunately, while these systems may offer new technologies in memory and computation, the general trend of memory performance is falling behind. With the added complexities of heterogeneous systems, achieving good memory performance is now becoming more difficult. Since different memory technologies exhibit various performance characteristics, careful memory management is required to consider tradeoffs in latency, bandwidth, capacity, and power. Application behavior, including data access patterns, data sizes, and operation types can indicate which characteristics limit the performance of an operation. However, understanding this information and using it to perform optimizations can be a difficult task. We expect this problem to become increasingly prevelent as the memory stack continues to change and expand. In this dissertation we present a solution to managing memory for these heterogeneous systems in an automated manner. We demonstrate its use on several applications and machine types, showcasing the benefit, flexibility, and expandability of the framework.
Issue Date:2019-12-03
Type:Text
URI:http://hdl.handle.net/2142/106362
Rights Information:Copyright 2019 Alex Brooks
Date Available in IDEALS:2020-03-02
Date Deposited:2019-12


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