Ziming Zhang, Yuting Chen, Venkatesh Saligrama
In this paper, we propose training very deep neural networks (DNNs) for supervised learning of hash codes. Existing methods in this context train relatively "shallow" networks limited by the issues arising in back propagation (vanishing gradients) as well as computational efficiency. We propose a novel and efficient training algorithm inspired by alternating direction method of […]
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Vijay J.Bodake, D.B.Bangal, K.B.Dhatrak
With the development of the GPGPU (General-purpose computing on graphics processing units), more and more computing problems are solved by using the parallel property of GPU (Graphics Processing Unit). CUDA (Compute Unified Device Architecture) is a framework which makes the GPGPU more accessible and easier to learn for the general population of programmers. This is […]
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Farzad Khorasani, Mehmet E. Belviranli, Rajiv Gupta, Laxmi N. Bhuyan
Hashing is one of the most fundamental operations that provides a means for a program to obtain fast access to large amounts of data. Despite the emergence of GPUs as many-threaded general purpose processors, high performance parallel data hashing solutions for GPUs are yet to receive adequate attention. Existing hashing solutions for GPUs not only […]
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Christian Lalanne, Servesh Muralidharan, Michael Lysaght
In this report, we present an OpenCL-based design of a hashing function which forms a core component of memcached [1], a distributed in-memory key-value store caching layer widely used to reduce access load between web servers and databases. Our work has been inspired by recent research investigations on dataflow architectures for key-value stores that can […]
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Tuan Tu Tran, Mathieu Giraud, Jean-Stephane Varre
Seed-based heuristics have proved to be efficient for studying similarity between genetic databases with billions of base pairs. This paper focuses on algorithms and data structures for the filtering phase in seed-based heuristics, with an emphasis on efficient parallel GPU/manycores implementation. We propose a 2-stage index structure which is based on neighborhood indexing and perfect […]
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Xiaojing An, Haojun Zhao, Lulu Ding, Zhongrui Fan, Hanyue Wang
RAR uses classic symmetric encryption algorithm SHA-1 hashing and AES algorithm for encryption, and the only method of password recovery is brute force, which is very time-consuming. In this paper, we present an approach using GPUs to speed up the password recovery process. However, because the major calculation and time-consuming part, SHA-1 hashing, is hard […]
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Markus Durmuth, Thorsten Kranz
Passwords are still by far the most widely used form of user authentication, for applications ranging from online banking or corporate network access to storage encryption. Password guessing thus poses a serious threat for a multitude of applications. Modern password hashes are specifically designed to slow down guessing attacks. However, having exact measures for the […]
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Marcos A. Simplicio Jr., Leonardo C. Almeida, Ewerton R. Andrade, Paulo C. F. dos Santos, and Paulo S. L. M. Barreto
We present Lyra2, a password hashing scheme (PHS) based on cryptographic sponges. Lyra2 was designed to be strictly sequential (i.e., not easily parallelizable), providing strong security even against attackers that uses multiple processing cores (e.g., custom hardware or a powerful GPU). At the same time, it is very simple to implement in software and allows […]
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Jason Michael Lowden
In an effort to provide security and data integrity, hashing algorithms have been designed to consume an input of any length to produce a fixed length output. KECCAK was selected by NIST to become the next Secure Hashing Algorithm SHA-3) after nearly five years of competition. In addition to providing a sequential operating mode, there […]
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A.B. Vavrenyuk, N.P. Vasilyev, V.V. Makarov, K.A. Matyukhin, M.M. Rovnyagin, A.A. Skitev
This article addresses problems of implementation of a modified Bloom filter as an additional module for mass data storage systems in supercomputers with hybrid CPU/GPU architecture. It is proposed to use a modified filter with counters, which makes it possible to monitor not only data addition, but also data removal. A comparative analysis has been […]
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Niko Lukac, Borut Zalik
The k-nearest neighbours (k-NN) search is one of the most critical nonparametric methods used in data retrieval and similarity tasks. Over recent years fast k-NN processing for large amount of high-dimensional data is increasingly demanded. Locality-sensitive hashing is a viable solution for computing fast approximate nearest neighbours (ANN) with reasonable accuracy. This chapter presents a […]
Jiong He, Mian Lu, Bingsheng He
Query co-processing on graphics processors (GPUs) has become an effective means to improve the performance of main memory databases. However, the relatively low bandwidth and high latency of the PCI-e bus are usually bottleneck issues for co-processing. Recently, coupled CPU-GPU architectures have received a lot of attention, e.g. AMD APUs with the CPU and the […]
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