No abstract

This paper presents the concept of dynamic control independence (DCl) and shows how it can be detected and exploited in an out-of-order superscalar processor to reduce the performance penalties of branch mispredictions. We show how DCI can be leveraged during branch misprediction recovery to reduce the number of instructions squashed on a misprediction as well as how it can be used to avoid predicting unpredictable branches by fetching instructions out-of-order A realistic implementation is described and evaluated using six SPECint95 benchmarks. We show that exploiting DCI during branch misprediction recovety improves pe$ormance by 0.9-9.9% on a I-wide processol; by I&11.2% on an b-wide processor and by 1.9-15.3% on a 12-wideprocessol: We also show that using DCI information to fetch instructions out-of-order when an unpredictable branch is encountered potentially improves performance by 0.9-15.2% on a I-wide processol: by 2.0-14.8% on an 8-wide processor and by 2.6-16.2% on a 12-wide processor: Some of the largest performance gains are observed on go and gee, which have traditionally posed the most d@cult challenge to aggressive branch prediction techniques.

No abstract

Network protocol stacks, in particular TCP/IP software implementations, are known for its inability to scale well in general-purpose monolithic operating systems (OS) for SMP. Previous researchers have experimented with affinitizing processes/thread, as well as interrupts from devices, to specific processors in a SMP system.However, general purpose operating systems have minimal consideration of userdefined affinity in their schedulers. Our goal is to expose the full potential of affinity by in-depth characterization of the reasons behind performance gains. We conducted an experimental study of TCP performance under various affinity modes on IA-based servers. Results showed that interrupt affinity alone provided a throughput gain of up to 25%, and combined thread/process and interrupt affinity can achieve gains of 30%. In particular, calling out the impact of affinity on machine clears (in addition to cache misses) is characterization that has not been done before.