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Scalable parallel computers for real-time signal processing

机译：可扩展的并行计算机，用于实时信号处理

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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 introduced.
机译：我们评估了大型并行处理器（MPP）中的最新技术及其在不同架构平台中的变化。在将MPP用于时间紧迫的应用（例如自适应雷达信号处理）时，发现了架构和编程问题。我们将审查支持技术。这些包括高性能CPU芯片和系统互连，分布式内存体系结构以及各种延迟隐藏机制。我们在三个方面描述可伸缩性的概念：资源，应用程序和技术。通过分析定义可扩展的性能属性。然后，我们将MPP与对称多处理器（SMP）和工作站集群（COW）进行比较。目的是揭示它们在信号处理中的能力，局限性和有效性。我们在MHPCC评估了IBM SP2，在SDSC评估了Intel Paragon，在Gray Eagan Center评估了Gray T3D，并评估了Intel提出的Gray T3E和ASCI TeraFLOP系统。在软件和编程方面，我们评估现有的并行编程环境，包括模型，语言，编译器，软件工具和操作系统。提供了一些程序并行化准则。我们研究数据并行，共享变量，消息传递和隐式编程模型。讨论了通信功能及其性能开销。还介绍了可用的软件工具和通信库。

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