Optimal Cache Partition-Sharing

2015 ◽  
Author(s):  
Jacob Brock ◽  
Chencheng Ye ◽  
Chen Ding ◽  
Yechen Li ◽  
Xiaolin Wang ◽  
...  
Keyword(s):  
Cache Partition

Machine-learning-based cache partition method in cloud environment

2021 ◽  
Author(s):  
Jiefan Qiu ◽  
Zonghan Hua ◽  
Lei Liu ◽  
Mingsheng Cao ◽  
Dajiang Chen
Keyword(s):  
Machine Learning ◽  
Cloud Environment ◽  
Partition Method ◽  
Cache Partition

Run-Time Cache-Partition Controller for Multi-Core Systems

2019 ◽  
Author(s):  
Jakob Danielsson ◽  
Marcus Jagemar ◽  
Moris Behnam ◽  
Tiberiu Seceleanu ◽  
Mikael Sjodin
Keyword(s):  
Run Time ◽  
Cache Partition

Dynamic Partition of Shared Cache for Multi-Thread Application in Multi-Core System

2010 ◽  
Vol 439-440 ◽  
pp. 1587-1594
Author(s):  
Shuo Li ◽  
Feng Wu
Keyword(s):  
System Performance ◽  
Scientific Computing ◽  
Chip Multiprocessor ◽  
Core System ◽  
Cache Partitioning ◽  
Shared Cache ◽  
Rate Information ◽  
Partitioning Algorithm ◽  
Cache Partition

In a chip-multiprocessor with a shared cache structure , the competing accesses from different applications degrade the system performance.The accesses degrade the performance and result in non-predicting executing time. Cache partitioning techniques can exclusively partition the shared cache among multiple competing applications. In this paper, the authors design the framework of Process priority-based Multithread Cache Partitioning(PP-MCP),a dynamic shared cache partitioning mechanism to improve the performance of multi-threaded multi-programmed workloads. The framework includes a miss rate monitor , called Application-oriented Miss Rate Monitor (AMRM) , which dynamically collect s miss rate information of multiple multi-threaded applications on different cache partitions , and process priority-based weighted cache partitioning algorithm ,which extends traditional miss rate oriented cache partition algorithms.The algorithm allocates Cache in sequence of the value of the process priority and it ensures that the highest priority process will get enough Cache space; and the applications with more threads tend to get more shared cache in order to improve t he overall system performance. Experiments show that PP-MCP has better IPC throughput and weighted speedup. Specifically , for multi-threaded multi-programmed scientific computing workloads , PP-MCP-1 improves throughput by up to 20% and on average 10 % over PP-MCP-0.

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