III: Small: Avoiding Contention on Multicore Machines

点击翻译按钮获取中文摘要

To take full advantage of the parallelism offered by a multicoremachine, one must write parallel code. Writing parallel code isdifficult. Even when one writes correct code, there are numerousperformance pitfalls. For example, an unrecognized data hotspot couldmean that all threads effectively serialize their access to thehotspot, and throughput is dramatically reduced.This project aims to provide a generic framework for performingcertain kinds of concurrent operations in parallel. Infrastructure isprovided to perform those operations in a scalable way over theavailable threads in a multicore machine, automatically responding tohotspots and other performance hazards. The goal is not to squeezethe last drop of performance out of a particular platform. Rather,with the planned system a programmer can, without detailed knowledgeof concurrent and parallel programming, develop code that efficientlyutilizes a multicore machine.The project involves the development of algorithms and data structuresdesigned for the efficient parallel execution of generic codefragments. The primary focus is on data intensive operations as wouldtypically be found in an in-memory database engine. Critical researchquestions include how to design generic multi-threaded operators thatcan be applied to a range of computations, how to avoid cachethrashing, and how to implement the framework in a way that works on avariety of hardware platforms. Performance improvements in throughputof an order of magnitude are expected relative to naive solutions thatsuffer from contention. The project aims to achieve performance closeto that of hand-tailored expert-written parallel code, with far lesscoding effort.This project has immediate applications in both commercial andpublic-domain database systems where performance improvements wouldenhance the experience of database system users, and reduce hardwareand energy requirements for a given level of performance.Programmability improvements would allow programmers without expertisein parallel programming to effectively use multicore machines. Theproject also provides the focus for an advanced-level course ondatabase system implementation for multicore machines. The softwareinfrastructure will be made available for research use by others.