Hybrid Network-on-Chip: An Application-Aware Framework for Big Data

Burst growing IoT and cloud computing demand exascale computing systems with high performance and low power consumption to process massive amounts of data. Modern system platforms based on fundamental requirements encounter a performance gap in chasing exponential growth in data speed and amount. To narrow the gap, a heterogamous design gives us a hint. A network-on-chip (NoC) introduces a packet-switched fabric for on-chip communication and becomes the de facto many-core interconnection mechanism; it refers to a vital shared resource for multifarious applications which will notably affect system energy efficiency. Among all the challenges in NoC, unaware application behaviors bring about considerable congestion, which wastes huge amounts of bandwidth and power consumption on the chip. In this paper, we propose a hybrid NoC framework, combining buffered and bufferless NoCs, to make the NoC framework aware of applications’ performance demands. An optimized congestion control scheme is also devised to satisfy the requirement in energy efficiency and the fairness of big data applications. We use a trace-driven simulator to model big data applications. Compared with the classical buffered NoC, the proposed hybrid NoC is able to significantly improve the performance of mixed applications by 17% on average and 24% at the most, decrease the power consumption by 38%, and improve the fairness by 13.3%

Tailoring the tribology property and corrosion resistance of selective laser melted CoCrMo alloys by varying copper content

In this study, the cobalt-chromium-molybdenum (CoCrMo) alloys containing varying Cu contents (CCM-xCu, x  = 0, 2, 3, 4 wt%) were fabricated via the selected laser melting (SLM) method. The influences of Cu content on tribological performance and corrosion resistance were investigated. The 2 and 3 wt% Cu contributed to inhibiting the generation of the HCP phase, whereas the inhibitory effect was quite limited at 4 wt% Cu. Notably, 4 wt% Cu led to the formation of Cr-enrich precipitates in the matrix, which was partially coherent with the Cu nanoparticle. The corrosion resistance of the CCM alloy was enhanced as the 2 and 3 wt% Cu added into the CCM alloy, contrarily, which deteriorated when Cu content reached 4 wt%. For the CCM-2Cu and CCM-3Cu, Cr-precipitates played a major role in enhancing the wear resistance, while the Cu lubrication effect working in coordination with Cr-precipitates determined that for the CCM-4Cu. This study was expected to achieve better tribology and corrosion properties of SLM-produced CCM alloys by tailoring microstructure through the Cu element