SHAMP: An experimental shared memory multimicroprocessor system for performance evaluation of parallel algorithms

In this paper, the design and implementation of a single shared bus, shared memory multiprocessing system using Intel's single board computers is presented. The hardware configuration and the operating system developed to execute the parallel algorithms are discussed. The performance evaluation studies carried out on Image are outlined.

Rotating Beams and Nonrotating Beams With Shared Eigenpair

In this paper, we look for rotating beams whose eigenpair (frequency and mode-shape) is the same as that of uniform nonrotating beams for a particular mode. It is found that, for any given mode, there exist flexural stiffness functions (FSFs) for which the jth mode eigenpair of a rotating beam, with uniform mass distribution, is identical to that of a corresponding nonrotating uniform beam with the same length and mass distribution. By putting the derived FSF in the finite element analysis of a rotating cantilever beam, the frequencies and mode-shapes of a nonrotating cantilever beam are obtained. For the first mode, a physically feasible equivalent rotating beam exists, but for higher modes, the flexural stiffness has internal singularities. Strategies for addressing the singularities in the FSF for finite element analysis are provided. The proposed functions can be used as test-functions for rotating beam codes and for targeted destiffening of rotating beams.

Parallel polygon scan conversion algorithms: Performance evaluation on a shared bus architecture

In this paper, three parallel polygon scan conversion algorithms have been proposed, and their performance when executed on a shared bus architecture has been compared. It has been shown that the parallel algorithm that does not use edge coherence performs better than those that use edge coherence. Further, a multiprocessing architecture has been proposed to execute the parallel polygon scan conversion algorithms more efficiently than a single shared bus architecture.

Design and evaluation of a dual-microcomputer shared memory system with a shared I/O bus

The design, implementation and evaluation are described of a dual-microcomputer system based on the concept of shared memory. Shared memory is useful for passing large blocks of data and it also provides a means to hold and work with shared data. In addition to the shared memory, a separate bus between the I/O ports of the microcomputers is provided. This bus is utilized for interprocessor synchronization. Software routines helpful in applying the dual-microcomputer system to realistic problems are presented. Performance evaluation of the system is carried out using benchmarks.

Hierarchical Directory-Based Shared Memory Architecture

We describe the design of a directory-based shared memory architecture on a hierarchical network of hypercubes. The distributed directory scheme comprises two separate hierarchical networks for handling cache requests and transfers. Further, the scheme assumes a single address space and each processing element views the entire network as contiguous memory space. The size of individual directories stored at each node of the network remains constant throughout the network. Although the size of the directory increases with the network size, the architecture is scalable. The results of the analytical studies demonstrate superior performance characteristics of our scheme compared with those of other schemes.

Pricing a Shared Access Link for Fair and Efficient Operation with Variable User Data Rates

The literature on pricing implicitly assumes an "infinite data" model, in which sources can sustain any data rate indefinitely. We assume a more realistic "finite data" model, in which sources occasionally run out of data; this leads to variable user data rates. Further, we assume that users have contracts with the service provider, specifying the rates at which they can inject traffic into the network. Our objective is to study how prices can be set such that a single link can be shared efficiently and fairly among users in a dynamically changing scenario where a subset of users occasionally has little data to send. User preferences are modelled by concave increasing utility functions. Further, we introduce two additional elements: a convex increasing disutility function and a convex increasing multiplicative congestion-penally function. The disutility function takes the shortfall (contracted rate minus present rate) as its argument, and essentially encourages users to send traffic at their contracted rates, while the congestion-penalty function discourages heavy users from sending excess data when the link is congested. We obtain simple necessary and sufficient conditions on prices for fair and efficient link sharing; moreover, we show that a single price for all users achieves this. We illustrate the ideas using a simple experiment.

Probabilistic Shared Cache Management (PriSM)

Effective sharing of the last level cache has a significant influence on the overall performance of a multicore system. We observe that existing solutions control cache occupancy at a coarser granularity, do not scale well to large core counts and in some cases lack the flexibility to support a variety of performance goals. In this paper, we propose Probabilistic Shared Cache Management (PriSM), a framework to manage the cache occupancy of different cores at cache block granularity by controlling their eviction probabilities. The proposed framework requires only simple hardware changes to implement, can scale to larger core count and is flexible enough to support a variety of performance goals. We demonstrate the flexibility of PriSM, by computing the eviction probabilities needed to achieve goals like hit-maximization, fairness and QOS. PriSM-HitMax improves performance by 18.7% over LRU and 11.8% over previously proposed schemes in a sixteen core machine. PriSM-Fairness improves fairness over existing solutions by 23.3% along with a performance improvement of 19.0%. PriSM-QOS successfully achieves the desired QOS targets.

Incentive Compatible Influence Maximization in Social Networks with Application to Viral Marketing

Information diffusion and influence maximization are important and extensively studied problems in social networks. Various models and algorithms have been proposed in the literature in the context of the influence maximization problem. A crucial assumption in all these studies is that the influence probabilities are known to the social planner. This assumption is unrealistic since the influence probabilities are usually private information of the individual agents and strategic agents may not reveal them truthfully. Moreover, the influence probabilities could vary significantly with the type of the information flowing in the network and the time at which the information is propagating in the network. In this paper, we use a mechanism design approach to elicit influence probabilities truthfully from the agents. Our main contribution is to design a scoring rule based mechanism in the context of the influencer-influencee model. In particular, we show the incentive compatibility of the mechanisms and propose a reverse weighted scoring rule based mechanism as an appropriate mechanism to use.

Basic features of current induced/shared by cables mounted on down conductors/towers during stroke interception

The telecommunication, broadcasting and other instrumented towers carry power and/or signal cables from their ground end to their upper regions. During a direct hit to the tower, significant induction can occur to these mounted cables. In order to provide adequate protection to the equipments connected to them, protection schemes have been evolved in the literature. Development of more effective protection schemes requires a quantitative knowledge on various parameters. However, such quantitative knowledge is difficult to find at present. Amongst several of these aspects, the present work aims to investigate on the two important aspects: (i) what would be the nature of the induced currents and (ii) what will be the current sharing if as per the practice, the sheath of the cable is connected to the down conductor/tower. These aspects will be useful in design of protection schemes and also in analyzing the field structure around instrumented towers.

Throughput analysis of primary and secondary networks in a shared IEEE 802.11 system

In this paper, we analyze the coexistence of a primary and a secondary (cognitive) network when both networks use the IEEE 802.11 based distributed coordination function for medium access control. Specifically, we consider the problem of channel capture by a secondary network that uses spectrum sensing to determine the availability of the channel, and its impact on the primary throughput. We integrate the notion of transmission slots in Bianchi's Markov model with the physical time slots, to derive the transmission probability of the secondary network as a function of its scan duration. This is used to obtain analytical expressions for the throughput achievable by the primary and secondary networks. Our analysis considers both saturated and unsaturated networks. By performing a numerical search, the secondary network parameters are selected to maximize its throughput for a given level of protection of the primary network throughput. The theoretical expressions are validated using extensive simulations carried out in the Network Simulator 2. Our results provide critical insights into the performance and robustness of different schemes for medium access by the secondary network. In particular, we find that the channel captures by the secondary network does not significantly impact the primary throughput, and that simply increasing the secondary contention window size is only marginally inferior to silent-period based methods in terms of its throughput performance.

Rotating beams and non-rotating beams with shared eigenpair for pinned-free boundary condition

In this paper we look for a rotating beam, with pinned-free boundary conditions, whose eigenpair (frequency and mode-shape) is same as that of a uniform non-rotating beam for a particular mode. It is seen that for any given mode, there exists a flexural stiffness function (FSF) for which the ith mode eigenpair of a rotating beam with uniform mass distribution, is identical to that of a corresponding non-rotating beam with same length and mass distribution. Inserting these derived FSF's in a finite element code for a rotating pinned-free beam, the frequencies and mode shapes of a non-rotating pinned-free beam are obtained. For the first mode, a physically realistic equivalent rotating beam is possible, but for higher modes, the FSF has internal singularities. Strategies for addressing these singularities in the FSF for finite element analysis are provided. The proposed functions can be used as test functions for rotating beam codes and also for targeted destiffening of rotating beams.

Optimal incentive timing strategies for product marketing on social networks

We consider the problem of devising incentive strategies for viral marketing of a product. In particular, we assume that the seller can influence penetration of the product by offering two incentive programs: a) direct incentives to potential buyers (influence) and b) referral rewards for customers who influence potential buyers to make the purchase (exploit connections). The problem is to determine the optimal timing of these programs over a finite time horizon. In contrast to algorithmic perspective popular in the literature, we take a mean-field approach and formulate the problem as a continuous-time deterministic optimal control problem. We show that the optimal strategy for the seller has a simple structure and can take both forms, namely, influence-and-exploit and exploit-and-influence. We also show that in some cases it may optimal for the seller to deploy incentive programs mostly for low degree nodes. We support our theoretical results through numerical studies and provide practical insights by analyzing various scenarios.

Multi-task learning using shared and task specific information

Multi-task learning solves multiple related learning problems simultaneously by sharing some common structure for improved generalization performance of each task. We propose a novel approach to multi-task learning which captures task similarity through a shared basis vector set. The variability across tasks is captured through task specific basis vector set. We use sparse support vector machine (SVM) algorithm to select the basis vector sets for the tasks. The approach results in a sparse model where the prediction is done using very few examples. The effectiveness of our approach is demonstrated through experiments on synthetic and real multi-task datasets.

Anonymous Authentication with Shared Secrets

Anonymity and authenticity are both important yet often conflicting security goals in a wide range of applications. On the one hand for many applications (say for access control) it is crucial to be able to verify the identity of a given legitimate party (a.k.a. entity authentication). Alternatively an application might require that no one but a party can communicate on its behalf (a.k.a. message authentication). Yet, on the other hand privacy concerns also dictate that anonymity of a legitimate party should be preserved; that is no information concerning the identity of parties should be leaked to an outside entity eavesdropping on the communication. This conflict becomes even more acute when considering anonymity with respect to an active entity that may attempt to impersonate other parties in the system. In this work we resolve this conflict in two steps. First we formalize what it means for a system to provide both authenticity and anonymity even in the presence of an active man-in-the-middle adversary for various specific applications such as message and entity authentication using the constructive cryptography framework of Mau11, MR11]. Our approach inherits the composability statement of constructive cryptography and can therefore be directly used in any higher-level context. Next we demonstrate several simple protocols for realizing these systems, at times relying on a new type of (probabilistic) Message Authentication Code (MAC) called key indistinguishable (KI) MACs. Similar to the key hiding encryption schemes of BBDP01] they guarantee that tags leak no discernible information about the keys used to generate them.

Strategic Marketing and Innovation Performance of Indian MSMEs

Micro Small and Medium Enterprises (MSMEs) is an integral part of the Indian industrial sector. The distinctive features of MSMEs are less capital investment and high labour absorption which has created unprecedented importance to this sector. As per the Development Commissioner of MSME, the sector has the credit of being the second highest in employment in India, which stands next to agricultural sector. The MSMEs are very much needed in efficiently allocating the enormous labour supply and scarce capital by implementing labour intensive production processes. Associated with this high growth rates, MSMEs are also facing a number of problems like sub-optimal scale of operation, technological obsolescence, supply chain inefficiencies, increasing domestic and global competition, fund shortages, change in manufacturing & marketing strategies, turbulent and uncertain market scenario. To survive with such issues and compete with large and global enterprises, MSMEs need to adopt innovative approaches in their regular business operations. Among the manufacturing sectors, we find that they are unable to focus themselves in the present competition. This paper presents a brief literature of work done in MSMEs, Innovation and Strategic marketing with reference to Indian manufacturing firms.