Scalable Parallel Computers for Real-Time Signal Processing

We assess the state-of-the-art technology in massively parallel processors (MPPs) and their variations in different architectural platforms. Architectural and programming issues are identified in using MPPs for time-critical applications such as adaptive radar signal processing. We review the enabling technologies. These include high-performance CPU chips and system interconnects, distributed memory architectures, and various latency hiding mechanisms. We characterize the concept of scalability in three areas: resources, applications, and technology. Scalable performance attributes are analytically defined. Then we compare MPPs with symmetric multiprocessors (SMPs) and clusters of workstations (COWs). The purpose is to reveal their capabilities, limits, and effectiveness in signal processing. We evaluate the IBM SP2 at MHPCC, the Intel Paragon at SDSC, the Gray T3D at Gray Eagan Center, and the Gray T3E and ASCI TeraFLOP system proposed by Intel. On the software and programming side, we evaluate existing parallel programming environments, including the models, languages, compilers, software tools, and operating systems. Some guidelines for program parallelization are provided. We examine data-parallel, shared-variable, message-passing, and implicit programming models. Communication functions and their performance overhead are discussed. Available software tools and communication libraries are also introducedpublished_or_final_versio

HPCCP/CAS Workshop Proceedings 1998

This publication is a collection of extended abstracts of presentations given at the HPCCP/CAS (High Performance Computing and Communications Program/Computational Aerosciences Project) Workshop held on August 24-26, 1998, at NASA Ames Research Center, Moffett Field, California. The objective of the Workshop was to bring together the aerospace high performance computing community, consisting of airframe and propulsion companies, independent software vendors, university researchers, and government scientists and engineers. The Workshop was sponsored by the HPCCP Office at NASA Ames Research Center. The Workshop consisted of over 40 presentations, including an overview of NASA's High Performance Computing and Communications Program and the Computational Aerosciences Project; ten sessions of papers representative of the high performance computing research conducted within the Program by the aerospace industry, academia, NASA, and other government laboratories; two panel sessions; and a special presentation by Mr. James Bailey

The CloudSME Simulation Platform and its Applications: A Generic Multi-cloud Platform for Developing and Executing Commercial Cloud-based Simulations

Simulation is used in industry to study a large variety of problems ranging from increasing the productivity of a manufacturing system to optimizing the design of a wind turbine. However, some simulation models can be computationally demanding and some simulation projects require time consuming experimentation. High performance computing infrastructures such as clusters can be used to speed up the execution of large models or multiple experiments but at a cost that is often too much for Small and Medium-sized Enterprises (SMEs). Cloud computing presents an attractive, lower cost alternative. However, developing a cloud-based simulation application can again be costly for an SME due to training and development needs, especially if software vendors need to use resources of different heterogeneous clouds to avoid being locked-in to one particular cloud provider. In an attempt to reduce the cost of development of commercial cloud-based simulations, the CloudSME Simulation Platform (CSSP) has been developed as a generic approach that combines an AppCenter with the workflow of the WS-PGRADE/gUSE science gateway framework and the multi-cloud-based capabilities of the CloudBroker Platform. The paper presents the CSSP and two representative case studies from distinctly different areas that illustrate how commercial multi-cloud-based simulations can be created

Management of SPMD based parallel processing on clusters of workstations

Current attempts to manage parallel applications on Clusters of Workstations (COWs) have either generally followed the parallel execution environment approach or been extensions to existing network operating systems, both of which do not provide complete or satisfactory solutions. The efficient and transparent management of parallelism within the COW environment requires enhanced methods of process instantiation, mapping of parallel process to workstations, maintenance of process relationships, process communication facilities, and process coordination mechanisms. The aim of this research is to synthesise, design, develop and experimentally study a system capable of efficiently and transparently managing SPMD parallelism on a COW. This system should both improve the performance of SPMD based parallel programs and relieve the programmer from the involvement into parallelism management in order to allow them to concentrate on application programming. It is also the aim of this research to show that such a system, to achieve these objectives, is best achieved by adding new special services and exploiting the existing services of a client/server and microkernel based distributed operating system. To achieve these goals the research methods of the experimental computer science should be employed. In order to specify the scope of this project, this work investigated the issues related to parallel processing on COWs and surveyed a number of relevant systems including PVM, NOW and MOSIX. It was shown that although the MOSIX system provide a number of good services related to parallelism management, none of the system forms a complete solution. The problems identified with these systems include: instantiation services that are not suited to parallel processing; duplication of services between the parallelism management environment and the operating system; and poor levels of transparency. A high performance and transparent system capable of managing the execution of SPMD parallel applications was synthesised and the specific services of process instantiation, process mapping and process interaction detailed. The process instantiation service designed here provides the capability to instantiate parallel processes using either creation or duplication methods and also supports multiple and group based instantiation which is specifically design for SPMD parallel processing. The process mapping service provides the combination of process allocation and dynamic load balancing to ensure the load of a COW remains balanced not only at the time a parallel program is initialised but also during the execution of the program. The process interaction service guarantees to maintain transparently process relationships, communications and coordination services between parallel processes regardless of their location within the COW. The combination of these services provides an original architecture and organisation of a system that is capable of fully managing the execution of SPMD parallel applications on a COW. A logical design of a parallelism management system was developed derived from the synthesised system and was shown that it should ideally be based on a distributed operating system employing the client server model. The client/server based distributed operating system provides the level of transparency, modularity and flexibility necessary for a complete parallelism management system. The services identified in the synthesised system have been mapped to a set of server processes including: Process Instantiation Server providing advanced multiple and group based process creation and duplication; Process Mapping Server combining load collection, process allocation and dynamic load balancing services; and Process Interaction Server providing transparent interprocess communication and coordination. A Process Migration Server was also identified as vital to support both the instantiation and mapping servers. The RHODOS client/server and microkernel based distributed operating system was selected to carry out research into the detailed design and to be used for the implementation this parallelism management system. RHODOS was enhanced to provide the required servers and resulted in the development of the REX Manager, Global Scheduler and Process Migration Manager to provide the services of process instantiation, mapping and migration, respectively. The process interaction services were already provided within RHODOS and only required some extensions to the existing Process Manager and IPC Managers. Through a variety of experiments it was shown that when this system was used to support the execution of SPMD parallel applications the overall execution times were improved, especially when multiple and group based instantiation services are employed. The RHODOS PMS was also shown to greatly reduce the programming burden experienced by users when writing SPMD parallel applications by providing a small set of powerful primitives specially designed to support parallel processing. The system was also shown to be applicable and has been used in a variety of other research areas such as Distributed Shared Memory, Parallelising Compilers and assisting the port of PVM to the RHODOS system. The RHODOS Parallelism Management System (PMS) provides a unique and creative solution to the problem of transparently and efficiently controlling the execution of SPMD parallel applications on COWs. Combining advanced services such as multiple and group based process creation and duplication; combined process allocation and dynamic load balancing; and complete COW wide transparency produces a totally new system that addresses many of the problems not addressed in other systems

The first ICASE/LARC industry roundtable: Session proceedings

The first 'ICASE/LaRC Industry Roundtable' was held on October 3-4, 1994, in Williamsburg, Virginia. The main purpose of the roundtable was to draw attention of ICASE/LaRC scientists to industrial research agendas. The roundtable was attended by about 200 scientists, 30% from NASA Langley; 20% from universities; 17% NASA Langley contractors (including ICASE personnel); and the remainder from federal agencies other than NASA Langley. The technical areas covered reflected the major research programs in ICASE and closely associated NASA branches. About 80% of the speakers were from industry. This report is a compilation of the session summaries prepared by the session chairmen

Architecture--Performance Interrelationship Analysis In Single/Multiple Cpu/Gpu Computing Systems: Application To Composite Process Flow Modeling

Current developments in computing have shown the advantage of using one or more Graphic Processing Units (GPU) to boost the performance of many computationally intensive applications but there are still limits to these GPU-enhanced systems. The major factors that contribute to the limitations of GPU(s) for High Performance Computing (HPC) can be categorized as hardware and software oriented in nature. Understanding how these factors affect performance is essential to develop efficient and robust applications codes that employ one or more GPU devices as powerful co-processors for HPC computational modeling. The present work analyzes and understands the intrinsic interrelationship of both hardware and software categories on computational performance for single and multiple GPU-enhanced systems using a computationally intensive application that is representative of a large portion of challenges confronting modern HPC. The representative application uses unstructured finite element computations for transient composite resin infusion process flow modeling as the computational core, characteristics and results of which reflect many other HPC applications via the sparse matrix system used for the solution of linear system of equations. This work describes these various software and hardware factors and how they interact to affect performance of computationally intensive applications enabling more efficient development and porting of High Performance Computing applications that includes current, legacy, and future large scale computational modeling applications in various engineering and scientific disciplines