Towards exascale computing systems

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The proposed research program will focus on issues pertaining to Exascale Computing that is, computing systems attaining performance that is 1000x the performance of the present day PFlop/s systems. Specifically, we shall focus on methods that will contribute in the realization of such systems through performance enhancing techniques applicable to interconnection networks, scheduling, and low power design All are critical issues and are researched intensively internationally. In a cluster system, the interconnect plays an important role in delivering data to the computations. Our research program will develop methods that deliver data to the computations carried out by the many cores of the system with a minimum of latency. We shall investigate both the send and the receive sides of the communication channel. At the send side, prediction will allow the hiding of the setting-up-the-channel overhead while at the receiving end, directly injecting the payload to a section of the storage hierarchy that is the closest (and the fastest) to the computation that will consume it ensures minimal delays. Concomitant to the delivering of data to the computation, is the scheduling of these computations especially in the era of many-core processors. For maximum efficiency, one needs to ensure that a computation scheduled on a particular core is not waiting for data, or instructions. Our objective is to develop methods ensuring that computations are optimally scheduled on the available resources. As far as power is concerned, our objective is to develop a design environment that will automatically produce low power systems utilizing the information that is present within the description of the computation. We are developing techniques that identify the portions of the system that are not active during portions of the computation, so they can be switched-off. We are targeting this environment for embedded systems, but also to specialized computation engines that will be part of hybrid nodes as we move to address the challenge of exascale systems.