Optimal Partitioning of Cache Memory
IEEE Transactions on Computers
CQoS: a framework for enabling QoS in shared caches of CMP platforms
Proceedings of the 18th annual international conference on Supercomputing
Fair Cache Sharing and Partitioning in a Chip Multiprocessor Architecture
Proceedings of the 13th International Conference on Parallel Architectures and Compilation Techniques
Pin: building customized program analysis tools with dynamic instrumentation
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
Architectural support for operating system-driven CMP cache management
Proceedings of the 15th international conference on Parallel architectures and compilation techniques
From chaos to QoS: case studies in CMP resource management
ACM SIGARCH Computer Architecture News
Proceedings of the 34th annual international symposium on Computer architecture
Adaptive insertion policies for high performance caching
Proceedings of the 34th annual international symposium on Computer architecture
QoS policies and architecture for cache/memory in CMP platforms
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A Framework for Providing Quality of Service in Chip Multi-Processors
Proceedings of the 40th Annual IEEE/ACM International Symposium on Microarchitecture
High performance cache replacement using re-reference interval prediction (RRIP)
Proceedings of the 37th annual international symposium on Computer architecture
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The presence of shared caches in current multicore processors may generate a lot of performance variability in multi-programmed environments. For applications with quality-of-service requirements, this performance variability may lead the programmer to be overly pessimistic about performance and reduce the application features and/or spend a lot of effort optimizing the algorithms. To solve this problem, there must be a way for the programmer to define a reasonable performance target and a guarantee that the actual performance is very unlikely to be below the targeted performance. We propose that the performance target be defined as the performance measured when each core runs a copy of the application, which we call self-performance. This study characterizes self-performance and explains how the shared-cache replacement policy can be modified for self-performance to be meaningful.