NoCo: ILP-based worst-case contention estimation for mesh real-time manycores

Manycores are capable of providing the computational demands required by functionally-advanced critical applications in domains such as automotive and avionics. In manycores a network-on-chip (NoC) provides access to shared caches and memories and hence concentrates most of the contention that tasks suffer, with effects on the worst-case contention delay (WCD) of packets and tasks' WCET. While several proposals minimize the impact of individual NoC parameters on WCD, e.g. mapping and routing, there are strong dependences among these NoC parameters. Hence, finding the optimal NoC configurations requires optimizing all parameters simultaneously, which represents a multidimensional optimization problem. In this paper we propose NoCo, a novel approach that combines ILP and stochastic optimization to find NoC configurations in terms of packet routing, application mapping, and arbitration weight allocation. Our results show that NoCo improves other techniques that optimize a subset of NoC parameters.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under grant TIN2015- 65316-P and the HiPEAC Network of Excellence. It also received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (agreement No. 772773). Carles Hernández is jointly supported by the MINECO and FEDER funds through grant TIN2014-60404-JIN. Jaume Abella has been partially supported by the Spanish Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. Enrico Mezzetti has been partially supported by the Spanish Ministry of Economy and Competitiveness under Juan de la Cierva-Incorporaci´on postdoctoral fellowship number IJCI-2016-27396.Peer ReviewedPostprint (author's final draft

State-of-the-art in Power Line Communications: from the Applications to the Medium

In recent decades, power line communication has attracted considerable attention from the research community and industry, as well as from regulatory and standardization bodies. In this article we provide an overview of both narrowband and broadband systems, covering potential applications, regulatory and standardization efforts and recent research advancements in channel characterization, physical layer performance, medium access and higher layer specifications and evaluations. We also identify areas of current and further study that will enable the continued success of power line communication technology.Comment: 19 pages, 12 figures. Accepted for publication, IEEE Journal on Selected Areas in Communications. Special Issue on Power Line Communications and its Integration with the Networking Ecosystem. 201

Characterizing Service Level Objectives for Cloud Services: Motivation of Short-Term Cache Allocation Performance Modeling

Service level objectives (SLOs) stipulate performance goals for cloud applications, microservices, and infrastructure. SLOs are widely used, in part, because system managers can tailor goals to their products, companies, and workloads. Systems research intended to support strong SLOs should target realistic performance goals used by system managers in the field. Evaluations conducted with uncommon SLO goals may not translate to real systems. Some textbooks discuss the structure of SLOs but (1) they only sketch SLO goals and (2) they use outdated examples. We mined real SLOs published on the web, extracted their goals and characterized them. Many web documents discuss SLOs loosely but few provide details and reflect real settings. Systematic literature review (SLR) prunes results and reduces bias by (1) modeling expected SLO structure and (2) detecting and removing outliers. We collected 75 SLOs where response time, query percentile and reporting period were specified. We used these SLOs to confirm and refute common perceptions. For example, we found few SLOs with response time guarantees below 10 ms for 90% or more queries. This reality bolsters perceptions that single digit SLOs face fundamental research challenges.This work was funded by NSF Grants 1749501 and 1350941.No embargoAcademic Major: Computer Science and EngineeringAcademic Major: Financ