CSR: Medium: Collaborative Research: Fast and Simple Concurrency Through Data-Abstraction Transactions

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This research project has the goal of making easier to build fast software for today's multicore computers. The computer revolution depends on software whose performance continually improves. When software performance stalls, it becomes much harder to solve big scientific problems (such as genome analysis or climate modeling), and harder to continue running the systems that are important to our society. Modern software must simultaneously use many processors running in parallel. This is much harder than using a single processor: coordination issues can cause serious errors, and methods that avoid errors tend to run slowly. This research shows that a new system, called data-abstraction software transactional memory, can avoid errors without performance compromise.Data-abstraction software transaction memory is a kind of software transactional memory (STM). The STM design allows software programs to run arbitrary transactions on memory objects. Since transactions are inherently isolated, a transaction-based program can avoid much of the detailed, error-prone reasoning about coordination that plagues ad-hoc parallel programs. Data-abstraction STM advances on conventional STM by tracking changes at the level of abstract methods on data objects, rather than memory words. The resulting system has the same ease of programming as conventional STM, but performs much faster. Where a conventional STM might track hundreds of memory words to ensure transaction isolation, a data-abstraction STM can track single words, or even nothing at all, since data abstractions can intelligently track the minimal information required to preserve their semantics.The research project builds a data-abstraction software transactional memory and uses it to construct several fast software applications. These applications, including a world-class-speed database, achieve strong transactional guarantees, and great performance, while remaining easy to program. Programmers using data-abstraction STMs will be able to build more high-performance software, with less potential for error, on today's best and most efficient hardware, helping us bring the benefits of the computer revolution to more aspects of modern life.