PLACES'10: The 3rd Workshop on Programmng Language Approaches to concurrency and Communication-Centric Software

Paphos, Cyprus. March 201

A survey of parallel execution strategies for transitive closure and logic programs

An important feature of database technology of the nineties is the use of parallelism for speeding up the execution of complex queries. This technology is being tested in several experimental database architectures and a few commercial systems for conventional select-project-join queries. In particular, hash-based fragmentation is used to distribute data to disks under the control of different processors in order to perform selections and joins in parallel. With the development of new query languages, and in particular with the definition of transitive closure queries and of more general logic programming queries, the new dimension of recursion has been added to query processing. Recursive queries are complex; at the same time, their regular structure is particularly suited for parallel execution, and parallelism may give a high efficiency gain. We survey the approaches to parallel execution of recursive queries that have been presented in the recent literature. We observe that research on parallel execution of recursive queries is separated into two distinct subareas, one focused on the transitive closure of Relational Algebra expressions, the other one focused on optimization of more general Datalog queries. Though the subareas seem radically different because of the approach and formalism used, they have many common features. This is not surprising, because most typical Datalog queries can be solved by means of the transitive closure of simple algebraic expressions. We first analyze the relationship between the transitive closure of expressions in Relational Algebra and Datalog programs. We then review sequential methods for evaluating transitive closure, distinguishing iterative and direct methods. We address the parallelization of these methods, by discussing various forms of parallelization. Data fragmentation plays an important role in obtaining parallel execution; we describe hash-based and semantic fragmentation. Finally, we consider Datalog queries, and present general methods for parallel rule execution; we recognize the similarities between these methods and the methods reviewed previously, when the former are applied to linear Datalog queries. We also provide a quantitative analysis that shows the impact of the initial data distribution on the performance of methods

On Designing Multicore-aware Simulators for Biological Systems

The stochastic simulation of biological systems is an increasingly popular technique in bioinformatics. It often is an enlightening technique, which may however result in being computational expensive. We discuss the main opportunities to speed it up on multi-core platforms, which pose new challenges for parallelisation techniques. These opportunities are developed in two general families of solutions involving both the single simulation and a bulk of independent simulations (either replicas of derived from parameter sweep). Proposed solutions are tested on the parallelisation of the CWC simulator (Calculus of Wrapped Compartments) that is carried out according to proposed solutions by way of the FastFlow programming framework making possible fast development and efficient execution on multi-cores.Comment: 19 pages + cover pag

Petri net models of program execution in data flow environments

The computer systems of the eighties are expected to be designed using powerful low-cost distributed parts to achieve increases in computing power and concurrency. The resulting complexity due to the interaction and communication between these parts requires new methods for the analysis of the behavior of these systems. One such class of architectures, based on the concept of data flow, is designed to exploit the inherent parallelism within a program. In these computers, traditional sequencing constraints are removed and an operation is enabled for execution as soon as its operands are available;A method for approximating the time required to execute a data flow program (assuming adequate computing resources) is described. This method is applied to the static program graph at compile time and yields a parameterized equation for execution time performance. Based on a Petri net analysis and combined with more traditional approaches, this method is recursively applied to abstract operations in the program graph using a top-down approach. While this approach may introduce approximations at each stage, the major benefit is a significant reduction over other techniques in the time required for the analysis

Data Flow Program Graphs

Data flow languages form a subclass of the languages which are based primarily upon function application (i.e., applicative languages). By data flow language we mean any applicative language based entirely upon the notion of data flowing from one function entity to another or any language that directly supports such flowing. This flow concept gives data flow languages the advantage of allowing program definitions to be represented exclusively by graphs. Graphical representations and their applications are the subject of this article

A compiler approach to scalable concurrent program design

The programmer's most powerful tool for controlling complexity in program design is abstraction. We seek to use abstraction in the design of concurrent programs, so as to separate design decisions concerned with decomposition, communication, synchronization, mapping, granularity, and load balancing. This paper describes programming and compiler techniques intended to facilitate this design strategy. The programming techniques are based on a core programming notation with two important properties: the ability to separate concurrent programming concerns, and extensibility with reusable programmer-defined abstractions. The compiler techniques are based on a simple transformation system together with a set of compilation transformations and portable run-time support. The transformation system allows programmer-defined abstractions to be defined as source-to-source transformations that convert abstractions into the core notation. The same transformation system is used to apply compilation transformations that incrementally transform the core notation toward an abstract concurrent machine. This machine can be implemented on a variety of concurrent architectures using simple run-time support. The transformation, compilation, and run-time system techniques have been implemented and are incorporated in a public-domain program development toolkit. This toolkit operates on a wide variety of networked workstations, multicomputers, and shared-memory multiprocessors. It includes a program transformer, concurrent compiler, syntax checker, debugger, performance analyzer, and execution animator. A variety of substantial applications have been developed using the toolkit, in areas such as climate modeling and fluid dynamics

Design and implementation of a high-performance stream-based computing platform on multigenerational GPUs

Lamilla Álvarez, P. (2010). Design and implementation of a high-performance stream-based computing platform on multigenerational GPUs. http://hdl.handle.net/10251/9116.Archivo delegad