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Team-oriented process programming
Team-oriented process programming promises to provide significant support for the planning, directing, and controlling of software engineering projects. In this paper we apply process programming to software engineering teams and show how this can provide powerful new capabilities for the management of software projects. We identify key issues which must be addressed to apply process programming to teams, and present our vision for team-oriented process programming
Hyperswitch communication network
The Hyperswitch Communication Network (HCN) is a large scale parallel computer prototype being developed at JPL. Commercial versions of the HCN computer are planned. The HCN computer being designed is a message passing multiple instruction multiple data (MIMD) computer, and offers many advantages in price-performance ratio, reliability and availability, and manufacturing over traditional uniprocessors and bus based multiprocessors. The design of the HCN operating system is a uniquely flexible environment that combines both parallel processing and distributed processing. This programming paradigm can achieve a balance among the following competing factors: performance in processing and communications, user friendliness, and fault tolerance. The prototype is being designed to accommodate a maximum of 64 state of the art microprocessors. The HCN is classified as a distributed supercomputer. The HCN system is described, and the performance/cost analysis and other competing factors within the system design are reviewed
Deep Space Network information system architecture study
The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control
GCC-Plugin for Automated Accelerator Generation and Integration on Hybrid FPGA-SoCs
In recent years, architectures combining a reconfigurable fabric and a
general purpose processor on a single chip became increasingly popular. Such
hybrid architectures allow extending embedded software with application
specific hardware accelerators to improve performance and/or energy efficiency.
Aiding system designers and programmers at handling the complexity of the
required process of hardware/software (HW/SW) partitioning is an important
issue. Current methods are often restricted, either to bare-metal systems, to
subsets of mainstream programming languages, or require special coding
guidelines, e.g., via annotations. These restrictions still represent a high
entry barrier for the wider community of programmers that new hybrid
architectures are intended for. In this paper we revisit HW/SW partitioning and
present a seamless programming flow for unrestricted, legacy C code. It
consists of a retargetable GCC plugin that automatically identifies code
sections for hardware acceleration and generates code accordingly. The proposed
workflow was evaluated on the Xilinx Zynq platform using unmodified code from
an embedded benchmark suite.Comment: Presented at Second International Workshop on FPGAs for Software
Programmers (FSP 2015) (arXiv:1508.06320
The "MIND" Scalable PIM Architecture
MIND (Memory, Intelligence, and Network Device) is an advanced parallel computer architecture for high performance computing and scalable embedded processing. It is a
Processor-in-Memory (PIM) architecture integrating both DRAM bit cells and CMOS logic devices on the same silicon die. MIND is multicore with multiple memory/processor nodes on
each chip and supports global shared memory across systems of MIND components. MIND is distinguished from other PIM architectures in that it incorporates mechanisms for efficient support of a global parallel execution model based on the semantics of message-driven multithreaded split-transaction processing. MIND is designed to operate either in conjunction with other conventional microprocessors or in standalone arrays of like devices. It also incorporates mechanisms for fault tolerance, real time execution, and active power management. This paper describes the major elements and operational methods of the MIND
architecture
Space Generic Open Avionics Architecture (SGOAA) reference model technical guide
This report presents a full description of the Space Generic Open Avionics Architecture (SGOAA). The SGOAA consists of a generic system architecture for the entities in spacecraft avionics, a generic processing architecture, and a six class model of interfaces in a hardware/software system. The purpose of the SGOAA is to provide an umbrella set of requirements for applying the generic architecture interface model to the design of specific avionics hardware/software systems. The SGOAA defines a generic set of system interface points to facilitate identification of critical interfaces and establishes the requirements for applying appropriate low level detailed implementation standards to those interface points. The generic core avionics system and processing architecture models provided herein are robustly tailorable to specific system applications and provide a platform upon which the interface model is to be applied
ARGES: an Expert System for Fault Diagnosis Within Space-Based ECLS Systems
ARGES (Atmospheric Revitalization Group Expert System) is a demonstration prototype expert system for fault management for the Solid Amine, Water Desorbed (SAWD) CO2 removal assembly, associated with the Environmental Control and Life Support (ECLS) System. ARGES monitors and reduces data in real time from either the SAWD controller or a simulation of the SAWD assembly. It can detect gradual degradations or predict failures. This allows graceful shutdown and scheduled maintenance, which reduces crew maintenance overhead. Status and fault information is presented in a user interface that simulates what would be seen by a crewperson. The user interface employs animated color graphics and an object oriented approach to provide detailed status information, fault identification, and explanation of reasoning in a rapidly assimulated manner. In addition, ARGES recommends possible courses of action for predicted and actual faults. ARGES is seen as a forerunner of AI-based fault management systems for manned space systems
MGSim - Simulation tools for multi-core processor architectures
MGSim is an open source discrete event simulator for on-chip hardware
components, developed at the University of Amsterdam. It is intended to be a
research and teaching vehicle to study the fine-grained hardware/software
interactions on many-core and hardware multithreaded processors. It includes
support for core models with different instruction sets, a configurable
multi-core interconnect, multiple configurable cache and memory models, a
dedicated I/O subsystem, and comprehensive monitoring and interaction
facilities. The default model configuration shipped with MGSim implements
Microgrids, a many-core architecture with hardware concurrency management.
MGSim is furthermore written mostly in C++ and uses object classes to represent
chip components. It is optimized for architecture models that can be described
as process networks.Comment: 33 pages, 22 figures, 4 listings, 2 table
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