MLP-Aware Runahead Threads in a Simultaneous Multithreading Processor
HiPEAC '09 Proceedings of the 4th International Conference on High Performance Embedded Architectures and Compilers
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Memory-level parallelism aware fetch policies for simultaneous multithreading processors
ACM Transactions on Architecture and Code Optimization (TACO)
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Probabilistic job symbiosis modeling for SMT processor scheduling
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ACM Transactions on Architecture and Code Optimization (TACO)
MLP-Aware instruction queue resizing: the key to power-efficient performance
ARCS'10 Proceedings of the 23rd international conference on Architecture of Computing Systems
Probabilistic modeling for job symbiosis scheduling on SMT processors
ACM Transactions on Architecture and Code Optimization (TACO)
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A thread executing on a simultaneous multithreading (SMT) processor that experiences a long-latency load will eventually stall while holding execution resources. Existing long-latency load aware SMT fetch policies limit the amount of resources allocated by a stalled thread by identifying long-latency loads and preventing the given thread from fetching more instructions - and in some implementations, instructions beyond the long-latency load may even be flushed which frees allocated resources. This paper proposes an SMT fetch policy that takes into account the available memory-level parallelism (MLP) in a thread. The key idea proposed in this paper is that in case of an isolated long-latency load, i.e., there is no MLP, the thread should be prevented from allocating additional resources. However, in case multiple independent logn-latency loads overlao, i.e., there is MLP, the thread should allocate as many resources as needed in order to fully expose the available MLP. The proposed MLP-aware fetch policy achieves better performance for MLP-intensive threads on a SMT processor and achieves a better overall balance between performance and fairness than previously proposed fetch policies.