Compensating mode conversion due to bend discontinuities through intentional trace asymmetry

In this letter, a comparative analysis is carried out between the mechanism of mode conversion in differential microstrip lines due to bend discontinuities on one side and trace asymmetry on the other side. With the help of equivalent modal circuits, a theoretical basis is provided for the idea to compensate the undesired common mode (CM), due to the presence of the bend, by intentionally designing asymmetric traces. As an application example, the proposed CM-reduction strategy is used in conjunction with another recently-presented wideband CM suppression filter for differential microstrip lines. It is shown that the proposed solution enhances the overall CM-reduction performance of the filter by some decibels, while preserving its transmission properties

Relaxing state-access constraints in stateful programmable data planes

Supporting the programming of stateful packet forwarding functions in hardware has recently attracted the interest of the research community. When designing such switching chips, the challenge is to guarantee the ability to program functions that can read and modify data plane's state, while keeping line rate performance and state consistency. Current state-of-the-art designs are based on a very conservative all-or-nothing model: programmability is limited only to those functions that are guaranteed to sustain line rate, with any traffic workload. In effect, this limits the maximum time to execute state update operations. In this paper, we explore possible options to relax these constraints by using simulations on real traffic traces. We then propose a model in which functions can be executed in a larger but bounded time, while preventing data hazards with memory locking. We present results showing that such flexibility can be supported with little or no throughput degradation.Comment: 6 page

Estimating the Potential Speedup of Computer Vision Applications on Embedded Multiprocessors

Computer vision applications constitute one of the key drivers for embedded multicore architectures. Although the number of available cores is increasing in new architectures, designing an application to maximize the utilization of the platform is still a challenge. In this sense, parallel performance prediction tools can aid developers in understanding the characteristics of an application and finding the most adequate parallelization strategy. In this work, we present a method for early parallel performance estimation on embedded multiprocessors from sequential application traces. We describe its implementation in Parana, a fast trace-driven simulator targeting OpenMP applications on the STMicroelectronics' STxP70 Application-Specific Multiprocessor (ASMP). Results for the FAST key point detector application show an error margin of less than 10% compared to the reference cycle-approximate simulator, with lower modeling effort and up to 20x faster execution time.Comment: Presented at DATE Friday Workshop on Heterogeneous Architectures and Design Methods for Embedded Image Systems (HIS 2015) (arXiv:1502.07241

Asymmetric Leakage from Multiplier and Collision-Based Single-Shot Side-Channel Attack

The single-shot collision attack on RSA proposed by Hanley et al. is studied focusing on the difference between two operands of multiplier. It is shown that how leakage from integer multiplier and long-integer multiplication algorithm can be asymmetric between two operands. The asymmetric leakage is verified with experiments on FPGA and micro-controller platforms. Moreover, we show an experimental result in which success and failure of the attack is determined by the order of operands. Therefore, designing operand order can be a cost-effective countermeasure. Meanwhile we also show a case in which a particular countermeasure becomes ineffective when the asymmetric leakage is considered. In addition to the above main contribution, an extension of the attack by Hanley et al. using the signal-processing technique of Big Mac Attack is presented

Memory probes:Exploring retrospective user experience through traces of use on cherished objects

Our daily interactions with objects can not only leave traces of use on the objects but also leave memories in our minds. These human traces on objects are potential cues that can trigger our autobiographical memories and connect us to social networks. The first aim of this paper is to demonstrate what might be a suitable method of inquiry into the way materials can enrich dialogues about remembered experiences derived from human traces left on cherished possessions. The second aim is to investigate how the accumulation of human traces on objects influences people’s remembering and usage. The design of our research artifacts, Memory Probes, was situated in relation to three spectra of paired values: (1) the familiarity and strangeness of tool use, (2) the definiteness and ambiguity of data capture, and (3) the objective and subjective reality of interpretation. Our field study revealed a transactive nature between traces of interaction with possessions and memories in the owners’ minds. It also informed us of how gradual and curiosity-driven understanding could become a methodological nuance when we are empathetically engaged in a collaborative way of knowing with other participants. To conclude, several implications for designing products that can participate in our everyday reminiscing and meaning-making are proposed

Small-World File-Sharing Communities

Web caches, content distribution networks, peer-to-peer file sharing networks, distributed file systems, and data grids all have in common that they involve a community of users who generate requests for shared data. In each case, overall system performance can be improved significantly if we can first identify and then exploit interesting structure within a community's access patterns. To this end, we propose a novel perspective on file sharing based on the study of the relationships that form among users based on the files in which they are interested. We propose a new structure that captures common user interests in data--the data-sharing graph-- and justify its utility with studies on three data-distribution systems: a high-energy physics collaboration, the Web, and the Kazaa peer-to-peer network. We find small-world patterns in the data-sharing graphs of all three communities. We analyze these graphs and propose some probable causes for these emergent small-world patterns. The significance of small-world patterns is twofold: it provides a rigorous support to intuition and, perhaps most importantly, it suggests ways to design mechanisms that exploit these naturally emerging patterns