The METR technical reports are published as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract. We discuss how common problems arising with multi/manycore distributed architectures can be effectively handled through co-design of parallel/distributed programming abstractions and of autonomic management of non-functional concerns. In particular, we demonstrate how restricted parallel/distributed patterns (or skeletons) may be efficiently managed by rule-based autonomic managers. We discuss the basic principles underlying pattern+manager co-design, current implementations inspired by this approach and some results achieved with a proof-of-concept prototype.

The METR technical reports are published as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.

The METR technical reports are published as a means to ensure timely dissemination of scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract. Skeletal parallel programming enables us to develop parallel programs easily by composing ready-made components called skeletons. However, a simplycomposed skeleton program often lacks efficiency due to overheads of intermediate data structures and communications. Many studies have focused on optimizations by fusing successive skeletons to eliminate the overheads. Existing fusion transformations, however, are too general to achieve adequate efficiency for some classes of problems. Thus, a specific fusion optimization is needed for a specific class. In this paper, we propose a strategy for domain-specific optimization of skeleton programs. In this strategy, one starts with a normal form that abstracts the programs of interest, then develops fusion rules that transform a skeleton program into the normal form, and finally makes efficient parallel implementation of the normal form. We illustrate the strategy with a case study: optimization of skeleton programs involving neighbor elements, which is often seen in scientific computations. 1

Abstract — Pattern operators are extensions to the Pattern/Skeleton parallel programming approach used to apply two types of communication patterns to the same data. The operators are intended to simplify the wide range of possible patterns and skeletons. The abstraction helps manage non-functional concerns on the Grid/Cloud environments. This paper explains how the pattern operators work on synchronous cyclic undirected graph patterns, and it shows examples on how they are used. A prototype was created to test the feasibility of the idea. The example used to show the operator approach is the addition of termination detection to a discrete solution to a PDE. The example can be coded with 27.31 % less non-functional code than a similar implementation in MPJ, and its programmability index is 13.5 % compared to MPJ’s 9.85%. The overhead for an empty pattern with low communication was 15%. The use of pattern operators can reduce the number of skeletons/patterns developed.

Divide-and-conquer algorithms are suitable for modern parallel machines, tending to have large amounts of inherent parallelism and working well with caches and deep memory hierarchies. Among others, list homomorphisms are a class of recursive functions on lists, which match very well with the divide-and-conquer paradigm. However, direct programming with list homomorphisms is a challenge for many programmers. In this paper, we propose and implement a novel system that can automatically derive costoptimal list homomorphisms from a pair of sequential programs, based on the third homomorphism theorem. Our idea is to reduce extraction of list homomorphisms to derivation of weak right inverses. We show that a weak right inverse always exists and can be automatically generated from a wide class of sequential programs. We demonstrate our system with several nontrivial examples, including the maximum prefix sum problem, the prefix sum computation, the maximum segment sum problem, and the line-ofsight problem. The experimental results show practical efficiency of our automatic parallelization algorithm and good speedups of the generated parallel programs.

Abstract. FastFlow is a structured parallel programming framework targeting shared memory multi-core architectures. In this paper we introduce a FastFlow extension aimed at supporting a network of multi-core workstation as well. The extension supports the execution of FastFlow programs by coordinating–in a structured way–the fine grain parallel activities running on a single workstation. We discuss the design and the implementation of this extension presenting preliminary experimental results validating it on state-of-the-art networked multi-core nodes.