Memory performance of and-parallel prolog on shared-memory architectures

The goal of the RAP-WAM AND-parallel Prolog abstract architecture is to provide inference speeds significantly beyond those of sequential systems, while supporting Prolog semantics and preserving sequential performance and storage efficiency. This paper presents simulation results supporting these claims with special emphasis on memory performance on a two-level sharedmemory multiprocessor organization. Several solutions to the cache coherency problem are analyzed. It is shown that RAP-WAM offers good locality and storage efficiency and that it can effectively take advantage of broadcast caches. It is argued that speeds in excess of 2 ML IPS on real applications exhibiting medium parallelism can be attained with current technology

CoreTSAR: Task Scheduling for Accelerator-aware Runtimes

Heterogeneous supercomputers that incorporate computational accelerators such as GPUs are increasingly popular due to their high peak performance, energy efficiency and comparatively low cost. Unfortunately, the programming models and frameworks designed to extract performance from all computational units still lack the flexibility of their CPU-only counterparts. Accelerated OpenMP improves this situation by supporting natural migration of OpenMP code from CPUs to a GPU. However, these implementations currently lose one of OpenMP’s best features, its flexibility: typical OpenMP applications can run on any number of CPUs. GPU implementations do not transparently employ multiple GPUs on a node or a mix of GPUs and CPUs. To address these shortcomings, we present CoreTSAR, our runtime library for dynamically scheduling tasks across heterogeneous resources, and propose straightforward extensions that incorporate this functionality into Accelerated OpenMP. We show that our approach can provide nearly linear speedup to four GPUs over only using CPUs or one GPU while increasing the overall flexibility of Accelerated OpenMP

A bibliography on parallel and vector numerical algorithms

This is a bibliography of numerical methods. It also includes a number of other references on machine architecture, programming language, and other topics of interest to scientific computing. Certain conference proceedings and anthologies which have been published in book form are listed also

Dataflow development of medium-grained parallel software

PhD ThesisIn the 1980s, multiple-processor computers (multiprocessors) based on conven- tional processing elements emerged as a popular solution to the continuing demand for ever-greater computing power. These machines offer a general-purpose parallel processing platform on which the size of program units which can be efficiently executed in parallel - the "grain size" - is smaller than that offered by distributed computing environments, though greater than that of some more specialised architectures. However, programming to exploit this medium-grained parallelism remains difficult. Concurrent execution is inherently complex, yet there is a lack of programming tools to support parallel programming activities such as program design, implementation, debugging, performance tuning and so on. In helping to manage complexity in sequential programming, visual tools have often been used to great effect, which suggests one approach towards the goal of making parallel programming less difficult. This thesis examines the possibilities which the dataflow paradigm has to offer as the basis for a set of visual parallel programming tools, and presents a dataflow notation designed as a framework for medium-grained parallel programming. The implementation of this notation as a programming language is discussed, and its suitability for the medium-grained level is examinedScience and Engineering Research Council of Great Britain EC ERASMUS schem

Requirements for implementing real-time control functional modules on a hierarchical parallel pipelined system

Analysis of a robot control system leads to a broad range of processing requirements. One fundamental requirement of a robot control system is the necessity of a microcomputer system in order to provide sufficient processing capability.The use of multiple processors in a parallel architecture is beneficial for a number of reasons, including better cost performance, modular growth, increased reliability through replication, and flexibility for testing alternate control strategies via different partitioning. A survey of the progression from low level control synchronizing primitives to higher level communication tools is presented. The system communication and control mechanisms of existing robot control systems are compared to the hierarchical control model. The impact of this design methodology on the current robot control systems is explored

Parallel Architectures for Planetary Exploration Requirements (PAPER)

The Parallel Architectures for Planetary Exploration Requirements (PAPER) project is essentially research oriented towards technology insertion issues for NASA's unmanned planetary probes. It was initiated to complement and augment the long-term efforts for space exploration with particular reference to NASA/LaRC's (NASA Langley Research Center) research needs for planetary exploration missions of the mid and late 1990s. The requirements for space missions as given in the somewhat dated Advanced Information Processing Systems (AIPS) requirements document are contrasted with the new requirements from JPL/Caltech involving sensor data capture and scene analysis. It is shown that more stringent requirements have arisen as a result of technological advancements. Two possible architectures, the AIPS Proof of Concept (POC) configuration and the MAX Fault-tolerant dataflow multiprocessor, were evaluated. The main observation was that the AIPS design is biased towards fault tolerance and may not be an ideal architecture for planetary and deep space probes due to high cost and complexity. The MAX concepts appears to be a promising candidate, except that more detailed information is required. The feasibility for adding neural computation capability to this architecture needs to be studied. Key impact issues for architectural design of computing systems meant for planetary missions were also identified

A Pure Java Parallel Flow Solver

In this paper an overview is given on the "Have Java" project to attain a pure Java parallel Navier-Stokes flow solver (JParNSS) based on the thread concept and remote method invocation (RMI). The goal of this project is to produce an industrial flow solver running on an arbitrary sequential or parallel architecture, utilizing the Internet, capable of handling the most complex 3D geometries as well as flow physics, and also linking to codes in other areas such as aeroelasticity etc. Since Java is completely object-oriented the code has been written in an object-oriented programming (OOP) style. The code also includes a graphics user interface (GUI) as well as an interactive steering package for the parallel architecture. The Java OOP approach provides profoundly improved software productivity, robustness, and security as well as reusability and maintainability. OOP allows code construction similar to the aerodynamic design process because objects can be software coded and integrated, reflecting actual design procedures. In addition, Java is the programming language of the Internet and thus Java is the programming language of the Internet and thus Java objects on disparate machines or even separate networks can be connected. We explain the motivation for the design of JParNSS along with its capabilities that set it apart from other solvers. In the first two sections we present a discussion of the Java language as the programming tool for aerospace applications. In section three the objectives of the Have Java project are presented. In the next section the layer structures of JParNSS are discussed with emphasis on the parallelization and client-server (RMI) layers. JParNSS, like its predecessor ParNSS (ANSI-C), is based on the multiblock idea, and allows for arbitrarily complex topologies. Grids are accepted in GridPro property settings, grids of any size or block number can be directly read by JParNSS without any further modifications, requiring no additional preparation time for the solver input. In the last section, computational results are presented, with emphasis on multiprocessor Pentium and Sun parallel systems run by the Solaris operating system (OS)