12,922 research outputs found

    Modeling Data-Plane Power Consumption of Future Internet Architectures

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    With current efforts to design Future Internet Architectures (FIAs), the evaluation and comparison of different proposals is an interesting research challenge. Previously, metrics such as bandwidth or latency have commonly been used to compare FIAs to IP networks. We suggest the use of power consumption as a metric to compare FIAs. While low power consumption is an important goal in its own right (as lower energy use translates to smaller environmental impact as well as lower operating costs), power consumption can also serve as a proxy for other metrics such as bandwidth and processor load. Lacking power consumption statistics about either commodity FIA routers or widely deployed FIA testbeds, we propose models for power consumption of FIA routers. Based on our models, we simulate scenarios for measuring power consumption of content delivery in different FIAs. Specifically, we address two questions: 1) which of the proposed FIA candidates achieves the lowest energy footprint; and 2) which set of design choices yields a power-efficient network architecture? Although the lack of real-world data makes numerous assumptions necessary for our analysis, we explore the uncertainty of our calculations through sensitivity analysis of input parameters

    The "MIND" Scalable PIM Architecture

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    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

    Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

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    This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

    An Interactive System Level Simulation Environment for Systems- on-Chip

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    International audienceThis article presents an interactive simulation environment for high level models intended for Design Space Exploration of Systems-On-Chip. The existing open source development environment TTool supports the MARTE compliant UML profile DIPLODOCUS and enables the designer to create, simulate and formally verify models. The goal is to obtain first performance estimations of the system intended for design while minimizing the modeling effort. The contribution outlined in this paper is an additional module providing means for controlling the simulation in real time by performing step wise execution, saving and restoring simulation states as well as animating UML models of the system. Moreover the paper elaborates on the integration of these new features into the existing framework consisting of a simulation engine on the one hand and a graphical user interface on the other hand

    Methodologies for Designing Power-Aware Smart Card Systems

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    Smart cards are some of the smallest computing platforms in use today. They have limited resources, but a huge number of functional requirements. The requirement for multi-application cards increases the demand for high performance and security even more, whereas the limits given by size and energy consumption remain constant. We describe new methodologies for designing and implementing entire systems with regard to power awareness and required performance. To make use of this power-saving potential, also the higher layers of the system - the operating system layer and the application domain layer - are required to be designed together with the rest of the system. HW/SW co-design methodologies enable the gain of system-level optimization. The first part presents the abstraction of smart cards to optimize system architecture and memory system. Both functional and transactional-level models are presented and discussed. The proposed design flow and preliminary results of the evaluation are depicted. Another central part of this methodology is a cycle-accurate instruction-set simulator for secure software development. The underlaying energy model is designed to decouple instruction and data dependent energy dissipation, which leads to an independent characterization process and allows stepwise model refinement to increase estimation accuracy. The model has been evaluated for a high-performance smart card CPU and an use-case for secure software is given
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