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  1. Proceedings of the ACM SIGPLAN Workshop on Memory Systems Performance and Correctness (MSPC '13)
  2. A coldness metric for cache optimization
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APE: accelerator processor extensions to optimize data-compute co-location
A study of data structures with a deep heap shape
A low overhead method for recovering unused memory inside regions
Program-centric cost models for locality
Introducing kernel-level page reuse for high performance computing
Software-controlled transparent management of heterogeneous memory resources in virtualized systems
A new perspective on processing-in-memory architecture design
A coldness metric for cache optimization
All-window data liveness
Software-level scheduling to exploit non-uniformly shared data cache on GPGPU
Cache rationing for multicore
Analyzing locality of memory references in GPU architectures

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A coldness metric for cache optimization

Content Provider ACM Digital Library
Author Parihar, Raj Ding, Chen Huang, Michael C.
Abstract A "hot" concept in program optimization is hotness. For example, program optimization targets hot paths, and register allocation targets hot variables. Cache optimization, however, has to target cold data, which are less frequently used and tend to cause cache misses whenever they are accessed. Hot data, in contrast, as they are small and frequently used, tend to stay in cache. In this paper, we define a new metric called "coldness" and show how the coldness varies across programs and how much colder the data we have to optimize as the cache size on modern machines increases.
Starting Page 1
Ending Page 2
Page Count 2
File Format PDF
ISBN 9781450321037
DOI 10.1145/2492408.2492419
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2013-06-16
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Reuse distance Miss rate Coldness
Content Type Text
Resource Type Article
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