A Study of Deep Learning Robustness Against Computation Failures

For many types of integrated circuits, accepting larger failure rates in computations can be used to improve energy efficiency. We study the performance of faulty implementations of certain deep neural networks based on pessimistic and optimistic models of the effect of hardware faults. After identifying the impact of hyperparameters such as the number of layers on robustness, we study the ability of the network to compensate for computational failures through an increase of the network size. We show that some networks can achieve equivalent performance under faulty implementations, and quantify the required increase in computational complexity

Petrasonic, a musical exploration of Iowa's geology

Musical work for the Dossier “Creative practices in Sound Art” [note by editor]Link: https://youtube.com/playlist?list=PLXdYuKtwUhUrirWQ0B2X7XhfrBCGJVlG

Does the real GDP per capita convergence hold in the Common Market for Eastern and Southern Africa?

This article examines the convergence of real GDP per capita in the Common Market for Eastern and Southern Africa (COMESA) during the period 1950-2003. Income departures across countries were evaluated from several panel data unit root tests, especially we consider the absolute and conditional convergence. We find no evidence supporting the existence of convergence process for the income in the COMESA. Nevertheless, applying economic development criterion allows to identity two absolute convergence clubs into the COMESA, one for the most four developed countries (Egypt, Libya, Mauritius, Seychelles), and one other for the fourteen less developed ones. Thus, we show that most economies of COMESA are locked into a sustained poverty trap process.

Performance comparison between Java and JNI for optimal implementation of computational micro-kernels

General purpose CPUs used in high performance computing (HPC) support a vector instruction set and an out-of-order engine dedicated to increase the instruction level parallelism. Hence, related optimizations are currently critical to improve the performance of applications requiring numerical computation. Moreover, the use of a Java run-time environment such as the HotSpot Java Virtual Machine (JVM) in high performance computing is a promising alternative. It benefits from its programming flexibility, productivity and the performance is ensured by the Just-In-Time (JIT) compiler. Though, the JIT compiler suffers from two main drawbacks. First, the JIT is a black box for developers. We have no control over the generated code nor any feedback from its optimization phases like vectorization. Secondly, the time constraint narrows down the degree of optimization compared to static compilers like GCC or LLVM. So, it is compelling to use statically compiled code since it benefits from additional optimization reducing performance bottlenecks. Java enables to call native code from dynamic libraries through the Java Native Interface (JNI). Nevertheless, JNI methods are not inlined and require an additional cost to be invoked compared to Java ones. Therefore, to benefit from better static optimization, this call overhead must be leveraged by the amount of computation performed at each JNI invocation. In this paper we tackle this problem and we propose to do this analysis for a set of micro-kernels. Our goal is to select the most efficient implementation considering the amount of computation defined by the calling context. We also investigate the impact on performance of several different optimization schemes which are vectorization, out-of-order optimization, data alignment, method inlining and the use of native memory for JNI methods.Comment: Part of ADAPT Workshop proceedings, 2015 (arXiv:1412.2347

Risk-Taking Behavior with Limited Liability and Risk Aversion

The authors of this paper consider the problem of a risk-averse firm with limited liability. The firm has to select the size of its investment in a risky project. We show that the optimal exposure to risk of the limited liability firm is always larger than under full liability. Moreover, there exists a positive lower bound on the value of the firm below which the firm will "bet for resurrection," i.e. it will invest the largest positive amount in the risky project. We also consider the standard portfolio problem with more than one risky asset. We show that limited liability may induce the firm to specialize in no Mean-Variance efficient assets. This paper was presented at the Financial Institutions Center's May 1996 conference on "

Designing redundant metering valves for hydraulic actuators under mixability and low cost-constraints

This article deals with the design of redundant metering valves for mechanically signalled hydraulic actuators. The final aim of the work is to manufacture a new low-cost valve in replacement of the existing expensive valve with an additional leakage requirement in case of seizure. The new valve must ensure the same closed-loop behaviour of the actuator. The article presents the design of the valve according to the actuator specifications and to a criterion of mixability (capacity to replace the existing valve by a new one). The valve pre-design is based on the common sharp edges and rectangular orifice slots combined with a serial restrictor inserted on the supply line. After partial experimental validation, the proposed design process points out the interest of using a trapezoidal slot in order to get the required speed gain over the whole valve opening range. The proposal is validated through the experimental measurement of the actuator no-load speed as a function of the valve opening