Design Issues in General Purpose, Parallel Simulation Languages

This paper addresses the topic of designing general purpose, parallel simulation languages. We discuss how parallel simulation languages differ from general purpose programming languages. Our thesis is that the issues of distribution, performance, unusual implementation mechanism, and the desire for determinism are the dominant considerations in designing a simulation language today. We then discuss the separate roles that special and general purpose simulation languages play. Next we use the two languages, Sim++ and CPS, to illustrate these issues. Then we discuss eight design considerations: process versus event oriented-view, basic program structure, I/O, making implementation cost explicit to the programmer, providing dynamic facilities, memory management, the semantics of false messages in time warp, and program development methodology considerations. A number of conclusions are drawn from our experiences in language design

Overview of Hydra: a concurrent language for synchronous digital circuit design

Hydra is a computer hardware description language that integrates several kinds of software tool (simulation, netlist generation and timing analysis) within a single circuit specification. The design language is inherently concurrent, and it offers black box abstraction and general design patterns that simplify the design of circuits with regular structure. Hydra specifications are concise, allowing the complete design of a computer system as a digital circuit within a few pages. This paper discusses the motivations behind Hydra, and illustrates the system with a significant portion of the design of a basic RISC processor

Web Services: A Process Algebra Approach

It is now well-admitted that formal methods are helpful for many issues raised in the Web service area. In this paper we present a framework for the design and verification of WSs using process algebras and their tools. We define a two-way mapping between abstract specifications written using these calculi and executable Web services written in BPEL4WS. Several choices are available: design and correct errors in BPEL4WS, using process algebra verification tools, or design and correct in process algebra and automatically obtaining the corresponding BPEL4WS code. The approaches can be combined. Process algebra are not useful only for temporal logic verification: we remark the use of simulation/bisimulation both for verification and for the hierarchical refinement design method. It is worth noting that our approach allows the use of any process algebra depending on the needs of the user at different levels (expressiveness, existence of reasoning tools, user expertise)

The Scalability-Efficiency/Maintainability-Portability Trade-off in Simulation Software Engineering: Examples and a Preliminary Systematic Literature Review

Large-scale simulations play a central role in science and the industry. Several challenges occur when building simulation software, because simulations require complex software developed in a dynamic construction process. That is why simulation software engineering (SSE) is emerging lately as a research focus. The dichotomous trade-off between scalability and efficiency (SE) on the one hand and maintainability and portability (MP) on the other hand is one of the core challenges. We report on the SE/MP trade-off in the context of an ongoing systematic literature review (SLR). After characterizing the issue of the SE/MP trade-off using two examples from our own research, we (1) review the 33 identified articles that assess the trade-off, (2) summarize the proposed solutions for the trade-off, and (3) discuss the findings for SSE and future work. Overall, we see evidence for the SE/MP trade-off and first solution approaches. However, a strong empirical foundation has yet to be established; general quantitative metrics and methods supporting software developers in addressing the trade-off have to be developed. We foresee considerable future work in SSE across scientific communities.Comment: 9 pages, 2 figures. Accepted for presentation at the Fourth International Workshop on Software Engineering for High Performance Computing in Computational Science and Engineering (SEHPCCSE 2016

Mixing multi-core CPUs and GPUs for scientific simulation software

Recent technological and economic developments have led to widespread availability of multi-core CPUs and specialist accelerator processors such as graphical processing units (GPUs). The accelerated computational performance possible from these devices can be very high for some applications paradigms. Software languages and systems such as NVIDIA's CUDA and Khronos consortium's open compute language (OpenCL) support a number of individual parallel application programming paradigms. To scale up the performance of some complex systems simulations, a hybrid of multi-core CPUs for coarse-grained parallelism and very many core GPUs for data parallelism is necessary. We describe our use of hybrid applica- tions using threading approaches and multi-core CPUs to control independent GPU devices. We present speed-up data and discuss multi-threading software issues for the applications level programmer and o er some suggested areas for language development and integration between coarse-grained and ne-grained multi-thread systems. We discuss results from three common simulation algorithmic areas including: partial di erential equations; graph cluster metric calculations and random number generation. We report on programming experiences and selected performance for these algorithms on: single and multiple GPUs; multi-core CPUs; a CellBE; and using OpenCL. We discuss programmer usability issues and the outlook and trends in multi-core programming for scienti c applications developers

Simulation modelling and visualisation: toolkits for building artificial worlds

Simulations users at all levels make heavy use of compute resources to drive computational simulations for greatly varying applications areas of research using different simulation paradigms. Simulations are implemented in many software forms, ranging from highly standardised and general models that run in proprietary software packages to ad hoc hand-crafted simulations codes for very specific applications. Visualisation of the workings or results of a simulation is another highly valuable capability for simulation developers and practitioners. There are many different software libraries and methods available for creating a visualisation layer for simulations, and it is often a difficult and time-consuming process to assemble a toolkit of these libraries and other resources that best suits a particular simulation model. We present here a break-down of the main simulation paradigms, and discuss differing toolkits and approaches that different researchers have taken to tackle coupled simulation and visualisation in each paradigm