Distributed software transactional memory with clock validation on clusters

Abstract

Within a decade, multicore processors emerged and revolutionised the world of computing. Nowadays, even a low-end computer comes with a multi-core processor and is capable running multiple threads simultaneously. It becomes impossible to make the best computation power out from a computer with a single-threaded program. Meanwhile, writing multi-threaded software is daunting to a lot of programmers as the threads share data and involve complicated synchronisation techniques such as locks and conditions. Software transactional memory is a promising alternative model that programmers simply need to understand transactional consistency and segment code into transactions. Programming becomes exciting again, without races, deadlocks and other issues that are common in lock-based paradigms.

To pursue high throughput, performance-oriented computers have several multicore processors per each. A processor’s cache is not directly accessible by the cores in other processors, leading to non-uniform latency when the threads share data. These computers no longer behave like the classical symmetric multiprocessor computers. Although old programs continue to work, they do not necessary benefit from the added cores and caches. Most software transactional memory implementations fall into this category. They rely on a centralised and shared meta-variable (like logical clock) in order to provide the single-lock atomicity. On a computer with two or more multicore processors, the single and shared meta-variable gets regularly updated by different processors. This leads to a tremendous amount of cache contentions. Much time is spent on inter-processor cache invalidations rather than useful computations.

Nevertheless, as computers with four processors or more are exponentially complex and expensive, people would desire solving sophisticated problems with several smaller computers whenever possible. Supporting software transactional consistency across multiple computers is a rarely explored research area. Although we have similar mature research topics such as distributed shared memory and distributed relational database, they have remarkably different characteristics so that most of the implementation techniques and tricks are not applicable to the new system. There are several existing distributed software transactional memory systems, but we feel there is much room for improvement. One crucial area is the conflict detection mechanism. Some of these systems make use of broadcast messages to commit transactions, which are certainly not scalable for large-scale clusters. Others use directories to direct messages to the relevant nodes only, but they also keep visible reader lists for invalidation per node. Updating a shared reader lists involves cache invalidations on processors. Reading shared data on such systems are more expensive compared to the conventional low-cost invisible reader validation systems.

In this research, we aim to have a distributed software transactional memory system, with distributed clock validation for conflict detection purpose. As preparation, we first investigate some issues such as concurrency control and conflict detection in single-node systems. Finally, we combine the techniques with a tailor-made cache coherence protocol that is differentiated from typical distributed shared memory.