Application-Driven Network Performance Evaluation

先前对多处理器互连网络的研究主要集中在网络拓扑、交换机制和消息路由算法上，以最大限度地提高网络性能。很少有人研究并行应用程序通信特性的影响。通信模式、消息生成频率和消息大小是量化任何通信的三个属性。提出的研究旨在表征这些通信工作负载并分析它们对多处理器性能的影响。这项研究有两个主要阶段。在第一阶段，将通过收集来自并行机器和执行驱动的模拟器的执行跟踪，对广泛的并行应用程序进行流量分析。将对通信跟踪进行分析，以确定不同类型的通信模式、通信速率和通信量。该项目的第二阶段将利用这些真实的流量特性，通过仿真和分析模型对互联网络进行性能分析。将在这些工作负载下对各种拓扑结构上的已知单播和集合路由算法进行深入模拟。将开发捕获虫洞交换、虚拟通道流量控制、路由机制和实际工作负载的分析模型。该项目的主要贡献是描述用于不同架构和算法研究的应用程序工作负载。例如，对这些工作负载的评估将量化自适应路由算法的实际性能优势，将确定现有通信机制的潜在瓶颈，并将为开发特定于应用程序的路由算法提供见解。其次，新的数学工具将更准确地预测现实通信流量。本研究开发的技术和工具可用于理解和评估并行架构和算法之间的相互作用，以最大限度地提高现有机器的性能，并在未来设计更好的机器。

Prior research on multiprocessor interconnection networks has primarily focused on the network topology, switching mechanism, and message routing algorithm to maximize network performance. Very little work has been done to study the impact of the communication properties of parallel applications. Communication pattern, message generation frequency, and message size are the three attributes to quantify any communication. The proposed research is aimed at characterizing these communication workloads and analyzing their impact on multiprocessor performance. The research has two major phases. In the first phase, traffic profiling of a wide range of parallel applications will be conducted by collecting execution traces from parallel machines and also from an execution-driven simulator. The communication traces will be analyzed to determine different types of traffic patterns, rate of communication, and volume of communication. The second phase of the project will use these realistic traffic properties for the performance analysis of interconnection networks via simulation and analytic models. In-depth simulation of known unicast and collective routing algorithms on various topologies will be performed with these workloads. Analytical models capturing wormhole switching, virtual channel flow control, routing mechanism and the realistic workloads will be developed. The main contribution of the project is characterizing application workloads to be used for different architectural and algorithmic research. For example, evaluation with these workloads will quantify the actual performance advantages of adaptive routing algorithms, will identify the potential bottlenecks of existing communication mechanisms, and will provide insight for developing application-specific routing algorithms. Next, the new mathematical tools will be more accurate in predicting the realistic communication traffic. The techniques and tools developed in this research can be used in understandi ng and evaluating the interplay between parallel architectures and algorithms to maximize the performance of existing machines and to design better machines in the future.