Achieving Non-Inclusive Cache Performance with Inclusive Caches: Temporal Locality Aware (TLA) Cache Management Policies

2010 ◽  
Author(s):  
Aamer Jaleel ◽  
Eric Borch ◽  
Malini Bhandaru ◽  
Simon C. Steely Jr. ◽  
Joel Emer
Keyword(s):  
Cache Management ◽  
Cache Performance ◽  
Management Policies ◽  
Temporal Locality

SSD internal cache management policies: A survey

2021 ◽  
pp. 102334
Author(s):  
Shivani Tripathy ◽  
Manoranjan Satpathy
Keyword(s):  
Cache Management ◽  
Management Policies

Improving Cache Management Policies Using Dynamic Reuse Distances

2012 ◽  
Author(s):  
Nam Duong ◽  
Dali Zhao ◽  
Taesu Kim ◽  
Rosario Cammarota ◽  
Mateo Valero ◽  
...  
Keyword(s):  
Cache Management ◽  
Management Policies

CacheFlow: Cache Optimizations for Data Driven Multithreading

2006 ◽  
Vol 16 (02) ◽  
pp. 229-244 ◽  
Author(s):  
Costas Kyriacou ◽  
Paraskevas Evripidou ◽  
Pedro Trancoso
Keyword(s):  
Data Driven ◽  
Management Policy ◽  
Conflict Avoidance ◽  
Cache Management ◽  
Short Term ◽  
Simulation Experiments ◽  
Long Latency ◽  
Latency Tolerance ◽  
Management Policies ◽  
Access Patterns

Data-Driven Multithreading is a non-blocking multithreading model of execution that provides effective latency tolerance by allowing the computation processor do useful work, while a long latency event is in progress. With the Data-Driven Multithreading model, a thread is scheduled for execution only if all of its inputs have been produced and placed in the processor's local memory. Data-driven sequencing leads to irregular memory access patterns that could affect negatively cache performance. Nevertheless, it enables the implementation of short-term optimal cache management policies. This paper presents the implementation of CacheFlow, an optimized cache management policy which eliminates the side effects due to the loss of locality caused by the data-driven sequencing, and reduces further cache misses. CacheFlow employs thread-based prefetching to preload data blocks of threads deemed executable. Simulation results, for nine scientific applications, on a 32-node Data-Driven Multithreaded machine show an average speedup improvement from 19.8 to 22.6. Two techniques to further improve the performance of CacheFlow, conflict avoidance and thread reordering, are proposed and tested. Simulation experiments have shown a speedup improvement of 24% and 32%, respectively. The average speedup for all applications on a 32-node machine with both optimizations is 26.1.

Temporal locality and its impact on Web proxy cache performance

2000 ◽  
Vol 42 (2-3) ◽  
pp. 187-203 ◽  
Author(s):  
Anirban Mahanti ◽  
Derek Eager ◽  
Carey Williamson
Keyword(s):  
Cache Performance ◽  
Proxy Cache ◽  
Temporal Locality
Sign in / Sign up

Export Citation Format

Share Document