Chris C. Kirkham

The Manchester prototype dataflow computer

The Manchester project has developed a powerful dataflow processor based on dynamic tagging. This processor is large enough to tackle realistic applications and exhibits impressive speedup for programs with sufficient parallelism.

DiSTM: A Software Transactional Memory Framework for Clusters

While transactional memory (TM) research on shared-memory chip multiprocessors has been flourishing over the last years,limited research has been conducted in the cluster domain. In this paper,we introduce a research platform for exploiting software TMon clusters. The distributed software transactional memory (DiSTM) system has been designed for easy prototyping of TM coherence protocols and it does not rely on a software or hardware implementation of distributed shared memory. Three TM coherence protocols have been implemented and evaluated with established TM benchmarks. The decentralized transactional coherence and consistency protocol has been compared against two centralized protocols that utilize leases. Results indicate that depending on network congestion and amount of contention different protocols perform better.

Steal-on-Abort: Improving Transactional Memory Performance through Dynamic Transaction Reordering

In transactional memory, aborted transactions reduce performance, and waste computing resources. Ideally, concurrent execution of transactions should be optimally ordered to minimise aborts, but such an ordering is often either complex, or unfeasible, to obtain. This paper introduces a new technique called steal-on-abort , which aims to improve transaction ordering at runtime. Suppose transactions A and B conflict, and B is aborted. In general it is difficult to predict this first conflict, but once observed, it is logical not to execute the two transactions concurrently again. In steal-on-abort, the aborted transaction B is stolen by its opponent transaction A, and queued behind A to prevent concurrent execution of A and B. Without steal-on-abort, transaction B would typically have been restarted immediately, and possibly had a repeat conflict with transaction A. Steal-on-abort requires no application-specific information, modification, or offline pre-processing. In this paper, it is evaluated using a sorted linked list, red-black tree, STAMP-vacation, and Lee-TM. The evaluation reveals steal-on-abort is highly effective at eliminating repeat conflicts, which reduces the amount of computing resources wasted, and significantly improves performance.

Lee-TM: A Non-trivial Benchmark Suite for Transactional Memory

Transactional Memory (TM) is a concurrent programming paradigm that aims to make concurrent programming easier than fine-grain locking, whilst providing similar performance and scalability. Several TM systems have been made available for research purposes. However, there is a lack of a wide range of non-trivial benchmarks with which to thoroughly evaluate these TM systems. This paper introduces Lee-TM, a non-trivial and realistic TM benchmark suite based on Lees routing algorithm. The benchmark suite provides sequential, lock-based, and transactional implementations to enable direct performance comparison. Lees routing algorithm has several of the desirable properties of a non-trivial TM benchmark, such as large amounts of parallelism, complex contention characteristics, and a wide range of transaction durations and lengths. A sample evaluation shows unfavourable transactional performance and scalability compared to lock-based execution, in contrast to much of the published TM evaluations, and highlights the need for non-trivial TM benchmarks.

A Study of a Transactional Parallel Routing Algorithm

Transactional memory proposes an alternative synchronization primitive to traditional locks. Its promise is to simplify the software development of multi-threaded applications while at the same time delivering the performance of parallel applications using (complex and error prone) fine grain locking. This study reports our experience implementing a realistic application using transactional memory (TM). The application is Lees routing algorithm and was selected for its abundance of parallelism but difficulty of expressing it with locks. Each route between a source and a destination point in a grid can be considered a unit of parallelism. Starting from this simple approach, we evaluate the exploitable parallelism of a transactional parallel implementation and explore how it can be adapted to deliver better performance. The adaptations do not introduce locks nor alter the essence of the implemented algorithm, but deliver up to 20 times more parallelism. The adaptations are derived from understanding the application itself and TM. The evaluation simulates an abstracted TM system and, thus, the results are independent of specific software or hardware TM implemented, and describe properties of the application.

Advanced Concurrency Control for Transactional Memory Using Transaction Commit Rate

Concurrency control for Transactional Memory (TM) is investigated as a means for improving resource usage by adjusting dynamically the number of concurrently executing transactions. The proposed control system takes as feedback the measured Transaction Commit Rateto adjust the concurrency. Through an extensive evaluation, a new Concurrency Control Algorithm (CCA), called P-only Concurrency Control (PoCC), is shown to perform better than our other four proposed CCAs for a synthetic benchmark, and the STAMP and Lee-TM benchmarks.

Stored data structures on the Manchester dataflow machine

Experience with the Manchester Dataflow Machine has highlighted the importance of efficient handling of stored data structures in a practical parallel machine. It has proved necessary to add a special-purpose structure store to the machine, and this paper describes the role of this structure store and the software which uses it. Some key issues in data structure handling for parallel machines are raised.

Profiling Transactional Memory Applications

Transactional Memory (TM) has become an active research area as it promises to simplify the development of highly scalable parallel programs. Scalability is quickly becoming an essential software requirement as successive commodity processors integrate ever larger numbers of cores. Non-trivial TM applications to test TM implementations have only recently begun to emerge, but have been written in different programming languages, using different TM implementations, making analysis difficult.We ported the popular non-trivial TM applications from the STAMP suite (Genome, KMeans, and Vacation), and Lee-TM to DSTM2, a software TM implementation, and built into it a framework to profile their execution. This paper investigates which profiling information is most relevant to understanding the performance of these non-trivial TM applications using up to 8 processors. We report commonly used transactional execution metrics and introduce two new metrics that can be used to profile TM applications.

Exploiting the Correspondence between Micro Patterns and Class Names

This paper argues that semantic information encoded in natural language identifiers is a largely neglected resource for program analysis. First we show that words in Java class names relate to class properties, expressed using the recently developed micro patterns language. We analyse a large corpus of Java programs to create a database that links common class name words with micro patterns. Finally we report on prototype tools integrated with the Eclipse development environment. These tools use the database to inform programmers of particular problems or optimization opportunities in their code.

Investigating software Transactional Memory on clusters

Traditional parallel programming models achieve synchronization with error-prone and complex-to-debug constructs such as locks and barriers. Transactional Memory (TM) is a promising new parallel programming abstraction that replaces conventional locks with critical sections expressed as transactions. Most TM research has focused on single address space parallel machines, leaving the area of distributed systems unexplored. In this paper we introduce a flexible Java Software TM (STM) to enable evaluation and prototyping of TM protocols on clusters. Our STM builds on top of the ProActive framework and has as an underlying transactional engine the state-of-the-art DSTM2. It does not rely on software or hardware distributed shared memory for the execution. This follows the transactional semantics at object granularity level and its feasibility is evaluated with non-trivial TM-specific benchmarks.