Abstract

Higher yield, climbing transistor counts and shrinking dimensions of a single Integrated Circuit (IC) have always been the demands in the fabrication market. However, this increased complexity and miniaturization of transistors present a challenge, due to high critical process variations combined with a ubiquitous presence of temperature and supply voltage variations, to achieve the required specification bounds on the desired performance of the circuits. Since optimization has become a very crucial task in IC design, the paper presents an efficient transistor sizing based optimization technique of the CMOS circuits to achieve low power, high performance and high yield design goals. The proposed memetic algorithm judiciously utilizes a threshold based local search procedure to improve convergence in its inherent genetic nature. The algorithm optimizes with the effect of temperature ሾെ૞૞ܗܜ૞૛૚ሿԨ and supply voltage േ૚૙Ψ variations and in addition a number of statistically sampled sets generated as Gaussian, Latin Hypercube and Correlation Screened schemes of process variations. The proposed technique is applicable to any technology node and has been tested over several standard single-stage and some complex multi-stage digital circuits designed using a Multi-Gate high-K dielectric (MGK) 22nm CMOS model. The reduction in leakage power with propagation delay goes as high as ૞૜Ψ with ૢΨ respectively, as observed across the various digital circuits

Abstract

The formidable increase in the number of smaller and smarter embedded devices has compelled programmers to develop more and more specialized application programs for these systems. These resource intensive programs that have to be executed on limited memory systems make a strong case for compiler optimizations that reduce the executable size of programs. Standard compilers (like LLVM) offer an out-of-the-box -Oz optimization option—just a series of compiler optimization passes—that is specifically targeted for the reduction of the generated executable size. In this paper, we aim to analyze the effects of optimizations of LLVM compiler on the reduction of executable size. Specifically, we take the size of the executable as a metric and attempt to divide the -Oz series into logical groups and study their individual effects; while also study the effect of their combinations. Our preliminary study over SPEC CPU 2017 benchmarks gives us an insight into the comparative effect of the groups of passes on the executable size. Our work has potential to enable the user to tailor a custom series of passes so as to obtain the desired executable size

Abstract

Polar codes have a very good error correcting capacity compared to turbo and LDPC codes of similar length. They are the first to attain the channel capacity. The aim of the proposed work is to design an Area and Power optimal 2b SC polar decoder exhibiting reduced area and power without degrading the latency by iterative decomposition technique. The targeted performances in decoder architecture are achieved by novel reformulation of F-node, G-node and P-nodes.

Abstract

Sparse neural networks are efficient in both memory and compute when compared to dense neural networks. But on parallel hardware such as GPU, sparse neural networks result in small or no runtime performance gains. On the other hand, structured sparsity patterns like filter, channel and block sparsity result in large performance gains due to regularity induced by structure. Among structured sparsities, block sparsity is a generic structured sparsity pattern with filter and channel sparsity being sub cases of block sparsity. In this work, we focus on block sparsity and generate efficient block sparse convolutional neural networks using our approach DBSR (Dynamic block sparse reparameterization). Our DBSR approach, when applied on image classification task over Imagenet dataset, decreases parameters and FLOPS of ResneXt50 by a factor of 2x with only increase of 0.48 in Top-1 error. And when extended to the task of semantic segmentation, our approach reduces parameters and FLOPS by 30% and 20% respectively with only 1% decrease in mIoU for ERFNet over Cityscapes dataset

Abstract

In a distributed network, we consider two special nodes called the sender S and the receiver R that are connected by n node-disjoint (except for S and R) bi-directional wires. Out of these n wires, the adversary can control at most t wires (of its choice) in Byzantine fashion. In this setting, our goal is to design a message transmission protocol Π that assures the following two conditions hold: (1) by the end of the protocol Π, R gets the correct message m transmitted by S without any error (perfect reliability), and (2) the adversary learns no information aboutm, whatsoever, in information theoretic sense (perfect secrecy). Protocols that satisfy these two conditions are known as the Perfectly Secure Message Transmission (PSMT) protocols.

Abstract

The combination of two overlapping technologies (bigdata and cloud computing) helps easy access to the evolving applications. In this context, there is a serious requirement of ensuring the transmission of data securely in order to improve the productivity over the public channel. Since the data collected by various sources are strictly private and confidential, there is also a great requirement to deal with the privacy preservation of the bigdata. To handle this issue, a new privacy-preserving bigdata collection technique in cloud computing environment, called 2PBDC, has been designed, which allows secure communication between the bigdata gateway nodes and the cloud servers. 2PBDC is shown to be secure against various known attacks against an active/passive adversary through the formal security verification as well as informal security analysis. A detailed comparative study among 2PBDC and other existing schemes has been conducted. This study shows that 2PBDC offers a better trade-off among the security and functionality features and communication and computation overheads while these are compared with other schemes.

Abstract

Optical sensing for chemical analysis is emerging as it provides advantages such as good sensitivity, selectivity, electromagnetic immunity, etc. This work presents a low-cost, robust and easy to use technique for measurement of bulk water property changes, specifically pH, total dissolved solids (TDS), and turbidity. The designed multi-wavelength sensing mechanism is capable of measuring the absorption of light emitted by three different LEDs after passing through water. The optical responses obtained using this mechanism are then related to parameter changes of water for quality measurement. The results show that measurements for pH, TDS, and turbidity have a linear regression coefficient of 0.9691, 0.9729 and 0.76 respectively. By utilizing narrowband light sources of characteristic wavelengths for the target parameters, a compact and portable device can be designed for rapid measurements. This can work …

Abstract

The possibility of a quantum system to exhibit properties that are akin to both the classically held notions of being a particle and a wave, is one of the most intriguing aspects of the quantum description of nature. These aspects have been instrumental in understanding paradigmatic natural phenomena as well as to provide nonclassica applications. A conceptual foundation for the wave nature of a quantum state has recently been presented, through the notion of quantum coherence. We introduce here a parallel notion for the particle nature of a quantum state of an arbitrary physical situation. We provide hints towards a resource theory of particleness, and give a quantification of the same. Finally, we provide evidence for a complementarity between the particleness thus introduced, and the coherence of an arbitrary quantum state

Abstract

In this work, we exhaustively investigate 1 → 2 local and nonlocal broadcasting of entanglement as well as correlations beyond entanglement (geometric discord) using asymmetric Pauli cloners with most general two qubit state as the resource. We exemplify asymmetric broadcasting of entanglement using 'Maximally Entangled Mixed States'. We demonstrate the variation of broadcasting range with the amount of entanglement present in the resource state as well as with the asymmetry in the cloner. We show that it is impossible to optimally broadcast geometric discord with the help of these asymmetric Pauli cloning machines. We also study the problem of 1 → 3 broadcasting of entanglement using non-maximally entangled state (NME) as the resource. For this task, we introduce a method we call successive broadcasting which involves application of 1 → 2 optimal cloning machines multiple times. We compare and contrast the performance of this method with the application of direct 1 → 3 optimal cloning machines. We show that 1 → 3 optimal cloner does a better job at broadcasting than the successive application of 1 → 2 cloners and the successive method can be beneficial in the absence of 1 → 3 cloners. We also bring out the fundamental difference between the tasks of cloning and broadcasting in the final part of the manuscript. We create examples to show that there exist local unitaries which can be employed to give a better range for broadcasting. Such unitary operations are not only economical, but also surpass the best possible range obtained using existing cloning machines enabling broadcasting of lesser entangled states. This result opens up a new direction in exploration of methods to facilitate broadcasting which may outperform the standard strategies implemented through cloning transformations

Abstract

In this work, we extensively study the problem of broadcasting of entanglement as state dependent versus state independent cloners. We start by re-conceptualizing the idea of state dependent quantum cloning machine (SD-QCM), and in that process, we introduce different types of SD-QCMs, namely, orthogonal and non-orthogonal cloners. We derive the conditions for which the fidelity of these cloners will become independent of the input state. We note that such a construction allows us to maximize the cloning fidelity at the cost of having partial information of the input state. In the discussion on broadcasting of entanglement, we start with a general two qubit state as our resource and later we consider a specific example of Bell diagonal state. We apply both state dependent and state independent cloners (orthogonal and non-orthogonal), locally and non locally, on input resource state and obtain a range for broadcasting of entanglement in terms of the input state parameters. Our results highlight several instances where the state dependent cloners outperform their state independent counterparts in broadcasting entanglement. Our study provides a comparative perspective on the broadcasting of entanglement via cloning in two qubit scenario, when we have some knowledge of the resource ensemble versus a situation when we have no such information