Parallel evaluation strategies for lazy data structures in Haskell

Conventional parallel programming is complex and error prone. To improve programmer productivity, we need to raise the level of abstraction with a higher-level programming model that hides many parallel coordination aspects. Evaluation strategies use non-strictness to separate the coordination and computation aspects of a Glasgow parallel Haskell (GpH) program. This allows the specification of high level parallel programs, eliminating the low-level complexity of synchronisation and communication associated with parallel programming. This thesis employs a data-structure-driven approach for parallelism derived through generic parallel traversal and evaluation of sub-components of data structures. We focus on evaluation strategies over list, tree and graph data structures, allowing re-use across applications with minimal changes to the sequential algorithm. In particular, we develop novel evaluation strategies for tree data structures, using core functional programming techniques for coordination control, achieving more flexible parallelism. We use non-strictness to control parallelism more flexibly. We apply the notion of fuel as a resource that dictates parallelism generation, in particular, the bi-directional flow of fuel, implemented using a circular program definition, in a tree structure as a novel way of controlling parallel evaluation. This is the first use of circular programming in evaluation strategies and is complemented by a lazy function for bounding the size of sub-trees. We extend these control mechanisms to graph structures and demonstrate performance improvements on several parallel graph traversals. We combine circularity for control for improved performance of strategies with circularity for computation using circular data structures. In particular, we develop a hybrid traversal strategy for graphs, exploiting breadth-first order for exposing parallelism initially, and then proceeding with a depth-first order to minimise overhead associated with a full parallel breadth-first traversal. The efficiency of the tree strategies is evaluated on a benchmark program, and two non-trivial case studies: a Barnes-Hut algorithm for the n-body problem and sparse matrix multiplication, both using quad-trees. We also evaluate a graph search algorithm implemented using the various traversal strategies. We demonstrate improved performance on a server-class multicore machine with up to 48 cores, with the advanced fuel splitting mechanisms proving to be more flexible in throttling parallelism. To guide the behaviour of the strategies, we develop heuristics-based parameter selection to select their specific control parameters

Feat: Functional Enumeration of Algebraic Types

In mathematics, an enumeration of a set S is a bijective function from (an initial segment of) the natural numbers to S. We define "functional enumerations" as efficiently computable such bijections. This paper describes a theory of functional enumeration and provides an algebra of enumerations closed under sums, products, guarded recursion and bijections. We partition each enumerated set into numbered, finite subsets. We provide a generic enumeration such that the number of each part corresponds to the size of its values (measured in the number of constructors). We implement our ideas in a Haskell library called testing-feat, and make the source code freely available. Feat provides efficient "random access" to enumerated values. The primary application is property-based testing, where it is used to define both random sampling (for example QuickCheck generators) and exhaustive enumeration (in the style of SmallCheck). We claim that functional enumeration is the best option for automatically generating test cases from large groups of mutually recursive syntax tree types. As a case study we use Feat to test the pretty-printer of the Template Haskell library (uncovering several bugs)

Efficient and Reasonable Object-Oriented Concurrency

Making threaded programs safe and easy to reason about is one of the chief difficulties in modern programming. This work provides an efficient execution model for SCOOP, a concurrency approach that provides not only data race freedom but also pre/postcondition reasoning guarantees between threads. The extensions we propose influence both the underlying semantics to increase the amount of concurrent execution that is possible, exclude certain classes of deadlocks, and enable greater performance. These extensions are used as the basis an efficient runtime and optimization pass that improve performance 15x over a baseline implementation. This new implementation of SCOOP is also 2x faster than other well-known safe concurrent languages. The measurements are based on both coordination-intensive and data-manipulation-intensive benchmarks designed to offer a mixture of workloads.Comment: Proceedings of the 10th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE '15). ACM, 201

Developing and Measuring Parallel Rule-Based Systems in a Functional Programming Environment

This thesis investigates the suitability of using functional programming for building parallel rule-based systems. A functional version of the well known rule-based system OPS5 was implemented, and there is a discussion on the suitability of functional languages for both building compilers and manipulating state. Functional languages can be used to build compilers that reflect the structure of the original grammar of a language and are, therefore, very suitable. Particular attention is paid to the state requirements and the state manipulation structures of applications such as a rule-based system because, traditionally, functional languages have been considered unable to manipulate state. From the implementation work, issues have arisen that are important for functional programming as a whole. They are in the areas of algorithms and data structures and development environments. There is a more general discussion of state and state manipulation in functional programs and how theoretical work, such as monads, can be used. Techniques for how descriptions of graph algorithms may be interpreted more abstractly to build functional graph algorithms are presented. Beyond the scope of programming, there are issues relating both to the functional language interaction with the operating system and to tools, such as debugging and measurement tools, which help programmers write efficient programs. In both of these areas functional systems are lacking. To address the complete lack of measurement tools for functional languages, a profiling technique was designed which can accurately measure the number of calls to a function , the time spent in a function, and the amount of heap space used by a function. From this design, a profiler was developed for higher-order, lazy, functional languages which allows the programmer to measure and verify the behaviour of a program. This profiling technique is designed primarily for application programmers rather than functional language implementors, and the results presented by the profiler directly reflect the lexical scope of the original program rather than some run-time representation. Finally, there is a discussion of generally available techniques for parallelizing functional programs in order that they may execute on a parallel machine. The techniques which are easier for the parallel systems builder to implement are shown to be least suitable for large functional applications. Those techniques that best suit functional programmers are not yet generally available and usable

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

Paphos, Cyprus. March 201

Logic programming in the context of multiparadigm programming: the Oz experience

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This article has two goals: to give a tutorial of logic programming in Oz and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We conclude with lessons learned from this work, a brief history of Oz, and many entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic Programming

Size-Change Termination as a Contract

Termination is an important but undecidable program property, which has led to a large body of work on static methods for conservatively predicting or enforcing termination. One such method is the size-change termination approach of Lee, Jones, and Ben-Amram, which operates in two phases: (1) abstract programs into "size-change graphs," and (2) check these graphs for the size-change property: the existence of paths that lead to infinite decreasing sequences. We transpose these two phases with an operational semantics that accounts for the run-time enforcement of the size-change property, postponing (or entirely avoiding) program abstraction. This choice has two key consequences: (1) size-change termination can be checked at run-time and (2) termination can be rephrased as a safety property analyzed using existing methods for systematic abstraction. We formulate run-time size-change checks as contracts in the style of Findler and Felleisen. The result compliments existing contracts that enforce partial correctness specifications to obtain contracts for total correctness. Our approach combines the robustness of the size-change principle for termination with the precise information available at run-time. It has tunable overhead and can check for nontermination without the conservativeness necessary in static checking. To obtain a sound and computable termination analysis, we apply existing abstract interpretation techniques directly to the operational semantics, avoiding the need for custom abstractions for termination. The resulting analyzer is competitive with with existing, purpose-built analyzers

Synchronous Digital Circuits as Functional Programs

Functional programming techniques have been used to describe synchronous digital circuits since the early 1980s and have proven successful at describing certain types of designs. Here we survey the systems and formal underpinnings that constitute this tradition. We situate these techniques with respect to other formal methods for hardware design and discuss the work yet to be done

PAEAN : portable and scalable runtime support for parallel Haskell dialects

Over time, several competing approaches to parallel Haskell programming have emerged. Different approaches support parallelism at various different scales, ranging from small multicores to massively parallel high-performance computing systems. They also provide varying degrees of control, ranging from completely implicit approaches to ones providing full programmer control. Most current designs assume a shared memory model at the programmer, implementation and hardware levels. This is, however, becoming increasingly divorced from the reality at the hardware level. It also imposes significant unwanted runtime overheads in the form of garbage collection synchronisation etc. What is needed is an easy way to abstract over the implementation and hardware levels, while presenting a simple parallelism model to the programmer. The PArallEl shAred Nothing runtime system design aims to provide a portable and high-level shared-nothing implementation platform for parallel Haskell dialects. It abstracts over major issues such as work distribution and data serialisation, consolidating existing, successful designs into a single framework. It also provides an optional virtual shared-memory programming abstraction for (possibly) shared-nothing parallel machines, such as modern multicore/manycore architectures or cluster/cloud computing systems. It builds on, unifies and extends, existing well-developed support for shared-memory parallelism that is provided by the widely used GHC Haskell compiler. This paper summarises the state-of-the-art in shared-nothing parallel Haskell implementations, introduces the PArallEl shAred Nothing abstractions, shows how they can be used to implement three distinct parallel Haskell dialects, and demonstrates that good scalability can be obtained on recent parallel machines.PostprintPeer reviewe

A robust algebraic framework for high-level music writing and programming

International audienceIn this paper, we present a new algebraic model for music programming : tiled musical graphs. It is based on the idea that the definition of musical objects : what they are, and the synchronization of these objects : when they should be played, are two orthogonal aspects of music programming that should be kept separate although handled in a combined way. This leads to the definition of an algebra of music objects : tiled music graphs, which can be combined by a single operator : the tiled product, that is neither sequential nor parallel but both. From a mathematical point of view, this algebra is known to be especially robust since it is an inverse monoid. Various operators such as the reset and the coreset projections derive from these algebra and turned out to be fairly useful for music modeling. From a programming point of view, it provide a high level domain specific language (DSL) that is both hierarchical and modular. This language is currently under implementation in the functional programming language Haskell. From an applicative point of view, various music modeling examples are provided to show how notes, chords, melodies, musical meters and various kind of interpretation aspects can easily and robustly be encoded in this formalism