150,557 research outputs found
Regular Expression Matching and Operational Semantics
Many programming languages and tools, ranging from grep to the Java String
library, contain regular expression matchers. Rather than first translating a
regular expression into a deterministic finite automaton, such implementations
typically match the regular expression on the fly. Thus they can be seen as
virtual machines interpreting the regular expression much as if it were a
program with some non-deterministic constructs such as the Kleene star. We
formalize this implementation technique for regular expression matching using
operational semantics. Specifically, we derive a series of abstract machines,
moving from the abstract definition of matching to increasingly realistic
machines. First a continuation is added to the operational semantics to
describe what remains to be matched after the current expression. Next, we
represent the expression as a data structure using pointers, which enables
redundant searches to be eliminated via testing for pointer equality. From
there, we arrive both at Thompson's lockstep construction and a machine that
performs some operations in parallel, suitable for implementation on a large
number of cores, such as a GPU. We formalize the parallel machine using process
algebra and report some preliminary experiments with an implementation on a
graphics processor using CUDA.Comment: In Proceedings SOS 2011, arXiv:1108.279
Optimisation of a parallel ocean general circulation model
Abstract. This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing rou- tines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel e?ciency of the model is adversely a?ected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers
An abstract machine for parallel graph reduction
technical reportAn abstract machine suitable for parallel graph reduction on a shared memory multiprocessor is described. Parallel programming is plagued with subtle race conditions resulting in deadlock or fatal system errors. Due to the nondeterministic nature of program execution the utilization of resources may vary from one run to another. The abstract machine has been designed for the efficient execution of normal order functional languages. The instructions proposed related to parallel activity are sensitive to load conditions and the current utilization of resources on the machine. The novel aspect of the architecture is the very simple set of instructions needed to control the complexities of parallel execution. This is an important step towards building a compiler for multiprocessor machines and to further language research in this area. Sample test programs hand coded in this instruction set show good performance on our 18 node BBN Butterfly as compared to a VAX 8600
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
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