1,931 research outputs found

    Parallel Exhaustive Search without Coordination

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    We analyze parallel algorithms in the context of exhaustive search over totally ordered sets. Imagine an infinite list of "boxes", with a "treasure" hidden in one of them, where the boxes' order reflects the importance of finding the treasure in a given box. At each time step, a search protocol executed by a searcher has the ability to peek into one box, and see whether the treasure is present or not. By equally dividing the workload between them, kk searchers can find the treasure kk times faster than one searcher. However, this straightforward strategy is very sensitive to failures (e.g., crashes of processors), and overcoming this issue seems to require a large amount of communication. We therefore address the question of designing parallel search algorithms maximizing their speed-up and maintaining high levels of robustness, while minimizing the amount of resources for coordination. Based on the observation that algorithms that avoid communication are inherently robust, we analyze the best running time performance of non-coordinating algorithms. Specifically, we devise non-coordinating algorithms that achieve a speed-up of 9/89/8 for two searchers, a speed-up of 4/34/3 for three searchers, and in general, a speed-up of k4(1+1/k)2\frac{k}{4}(1+1/k)^2 for any k1k\geq 1 searchers. Thus, asymptotically, the speed-up is only four times worse compared to the case of full-coordination, and our algorithms are surprisingly simple and hence applicable. Moreover, these bounds are tight in a strong sense as no non-coordinating search algorithm can achieve better speed-ups. Overall, we highlight that, in faulty contexts in which coordination between the searchers is technically difficult to implement, intrusive with respect to privacy, and/or costly in term of resources, it might well be worth giving up on coordination, and simply run our non-coordinating exhaustive search algorithms

    Thermal conductance of thin film YIG determined using Bayesian statistics

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    Thin film YIG (Y3_3Fe5_5O12_{12}) is a prototypical material for experiments on thermally generated pure spin currents and the spin Seebeck effect. The 3-omega method is an established technique to measure the cross-plane thermal conductance of thin films, but can not be used in YIG/GGG (Ga3_3Gd5_5O12_{12}) systems in its standard form. We use two-dimensional modeling of heat transport and introduce a technique based on Bayesian statistics to evaluate measurement data taken from the 3-omega method. Our analysis method allows us to study materials systems that have not been accessible with the conventionally used 3-omega analysis. Temperature dependent thermal conductance data of thin film YIG are of major importance for experiments in the field of spin-caloritronics. Here we show data between room temperature and 10 K for films covering a wide thickness range as well as the magnetic field effect on the thermal conductance between 10 K and 50 K

    Are You Tampering With My Data?

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    We propose a novel approach towards adversarial attacks on neural networks (NN), focusing on tampering the data used for training instead of generating attacks on trained models. Our network-agnostic method creates a backdoor during training which can be exploited at test time to force a neural network to exhibit abnormal behaviour. We demonstrate on two widely used datasets (CIFAR-10 and SVHN) that a universal modification of just one pixel per image for all the images of a class in the training set is enough to corrupt the training procedure of several state-of-the-art deep neural networks causing the networks to misclassify any images to which the modification is applied. Our aim is to bring to the attention of the machine learning community, the possibility that even learning-based methods that are personally trained on public datasets can be subject to attacks by a skillful adversary.Comment: 18 page

    Selective interlayer ferromagnetic coupling between the Cu spins in YBa2_2 Cu3_3 O7x_{7-x} grown on top of La0.7_{0.7} Ca0.3_{0.3} MnO3_3

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    Studies to date on ferromagnet/d-wave superconductor heterostructures focus mainly on the effects at or near the interfaces while the response of bulk properties to heterostructuring is overlooked. Here we use resonant soft x-ray scattering spectroscopy to reveal a novel c-axis ferromagnetic coupling between the in-plane Cu spins in YBa2_2 Cu3_3 O7x_{7-x} (YBCO) superconductor when it is grown on top of ferromagnetic La0.7_{0.7} Ca0.3_{0.3} MnO3_3 (LCMO) manganite layer. This coupling, present in both normal and superconducting states of YBCO, is sensitive to the interfacial termination such that it is only observed in bilayers with MnO_2but not with La0.7_{0.7} Ca0.3_{0.3} interfacial termination. Such contrasting behaviors, we propose, are due to distinct energetic of CuO chain and CuO2_2 plane at the La0.7_{0.7} Ca0.3_{0.3} and MnO2_2 terminated interfaces respectively, therefore influencing the transfer of spin-polarized electrons from manganite to cuprate differently. Our findings suggest that the superconducting/ferromagnetic bilayers with proper interfacial engineering can be good candidates for searching the theorized Fulde-Ferrel-Larkin-Ovchinnikov (FFLO) state in cuprates and studying the competing quantum orders in highly correlated electron systems.Comment: Please note the change of the title. Text might be slightly different from the published versio

    CacheZoom: How SGX Amplifies The Power of Cache Attacks

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    In modern computing environments, hardware resources are commonly shared, and parallel computation is widely used. Parallel tasks can cause privacy and security problems if proper isolation is not enforced. Intel proposed SGX to create a trusted execution environment within the processor. SGX relies on the hardware, and claims runtime protection even if the OS and other software components are malicious. However, SGX disregards side-channel attacks. We introduce a powerful cache side-channel attack that provides system adversaries a high resolution channel. Our attack tool named CacheZoom is able to virtually track all memory accesses of SGX enclaves with high spatial and temporal precision. As proof of concept, we demonstrate AES key recovery attacks on commonly used implementations including those that were believed to be resistant in previous scenarios. Our results show that SGX cannot protect critical data sensitive computations, and efficient AES key recovery is possible in a practical environment. In contrast to previous works which require hundreds of measurements, this is the first cache side-channel attack on a real system that can recover AES keys with a minimal number of measurements. We can successfully recover AES keys from T-Table based implementations with as few as ten measurements.Comment: Accepted at Conference on Cryptographic Hardware and Embedded Systems (CHES '17
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