Synchronous parallel kinetic Monte Carlo simulation of AL3SC precipitation

The main objective of the present work is to profound the applicability of a synchronous parallel kinetic Monte Carlo (spkMC) algorithm for simulating the nucleation of Al3Sc precipitates. Parallel processes communication is implemented through Message Passing Interface (MPI). Consequently, the capability of extending time and length scales of atomistic kinetic Monte Carlo (kMC) will be attested. Lastly, we present the results obtained from simulations of nucleation of Al3Sc precipitates, which include a comparative view between sequential and parallel algorithms

Parallel NPARC: Implementation and Performance

Version 3 of the NPARC Navier-Stokes code includes support for large-grain (block level) parallelism using explicit message passing between a heterogeneous collection of computers. This capability has the potential for significant performance gains, depending upon the block data distribution. The parallel implementation uses a master/worker arrangement of processes. The master process assigns blocks to workers, controls worker actions, and provides remote file access for the workers. The processes communicate via explicit message passing using an interface library which provides portability to a number of message passing libraries, such as PVM (Parallel Virtual Machine). A Bourne shell script is used to simplify the task of selecting hosts, starting processes, retrieving remote files, and terminating a computation. This script also provides a simple form of fault tolerance. An analysis of the computational performance of NPARC is presented, using data sets from an F/A-18 inlet study and a Rocket Based Combined Cycle Engine analysis. Parallel speedup and overall computational efficiency were obtained for various NPARC run parameters on a cluster of IBM RS6000 workstations. The data show that although NPARC performance compares favorably with the estimated potential parallelism, typical data sets used with previous versions of NPARC will often need to be reblocked for optimum parallel performance. In one of the cases studied, reblocking increased peak parallel speedup from 3.2 to 11.8

Name-passing calculi and crypto-primitives: A survey

The paper surveys the literature on high-level name-passing process calculi, and their extensions with cryptographic primitives. The survey is by no means exhaustive, for essentially two reasons. First, in trying to provide a coherent presentation of different ideas and techniques, one inevitably ends up leaving out the approaches that do not fit the intended roadmap. Secondly, the literature on the subject has been growing at very high rate over the years. As a consequence, we decided to concentrate on few papers that introduce the main ideas, in the hope that discussing them in some detail will provide sufficient insight for further reading

RELEASE: A High-level Paradigm for Reliable Large-scale Server Software

Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the rst six months. The project aim is to scale the Erlang's radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the e ectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene