Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

We present challenges faced in making a domain-specific language (DSL) for graph algorithms adapt to varying requirements of generating a spectrum of efficient parallel codes. Graph algorithms are at the heart of several applications, and achieving high performance on graph applications has become critical due to the tremendous growth of irregular data. However, irregular algorithms are quite challenging to auto-parallelize, due to access patterns influenced by the input graph - which is unavailable until execution. Former research has addressed this issue by designing DSLs for graph algorithms, which restrict generality but allow efficient codegeneration for various backends. Such DSLs are, however, too rigid, and do not adapt to changes. For instance, these DSLs are incapable of changing the way of processing if the underlying graph changes. As another instance, most of the DSLs do not support more than one backends. We narrate our experiences in making an existing DSL, named Falcon, adaptive. The biggest challenge in the process is to retain the DSL code for specifying the underlying algorithm, and still generate different backend codes. We illustrate the effectiveness of our proposal by auto-generating codes for vertex-based versus edge-based graph processing, synchronous versus asynchronous execution, and CPU versus GPU backends from the same specification. © 2020 Association for Computing Machinery.

World University root node

Department of Computer Science and Engineering

GPGPU 2020 - Proceedings of the 2020 General Purpose Processing Using GPU

Custom code generation for a graph DSL

Distributed Graph Analytics

Graph Analytics Frameworks

The United Arab Emirates (UAE) has been experiencing the need for higher growth in gross domestic product (GDP) over the last few years. This growth necessitates the investments in major construction projects over the next few years. Unlike the projects in other industries, construction projects subjected to unique characteristics increase the probability of risks occurrence and their impact on achieving project objectives. Design stage was found to have a significant role in managing the risks during the project’s lifecycle. However; key challenges arise from the facts that the design phase has a numerous of interdependent, knowledge intensive multidisciplinary tasks and the overall process is inherently iterative in nature. This poor design interface management leads to project time overrun, cost overrun and poor quality output. Many tools and methods have been developed for the design information management. However these methods are not widely used except the building information modeling (BIM). Construction industry has benefited in many areas through BIM, and a natural consequent is to investigate its capabilities in managing risks. Literature review revealed that the existing BIM-based risk management frameworks required further development to manage the design phase related risks impacting the time, cost and quality of DBB projects. This paper proposed a conceptual BIM-based risk management framework to manage the design phase related risks for DBB high rise building projects in UAE. A framework has been validated through a case study. The results show that the risks can be effectively mitigated by implementing the proposed framework. © 2020, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.

Department of Civil Engineering

International Journal of Systems Assurance Engineering and Management

BIM based risk management for design bid build (DBB) design process in the United Arab Emirates: a conceptual framework

Purpose: The purpose of this paper is to explore, using fine-grained exploratory multi-case studies, organisational learning practices – and associated constraints – impacting the performance of four small- and medium-sized project organisations which deliver energy efficiency projects in South Africa and whose learning practice mixes are of wider significance for the emerging project society in the region. Design/methodology/approach: The unit of analysis is the Energy Efficiency Demand Side Management (EEDSM) programme; a US$104m grant funded the initiative directed at supporting energy efficient retro-fit projects across local municipalities in South Africa. Thematic analysis is undertaken, based on multiple exploratory interviews with project practitioners working for small- and medium-sized EEDSM project organisations. Findings: Recognising the criticality of tacit knowledge as a focus for learning, within unstructured, novel, non-routine and technically specialised learning contexts in particular, the widespread lack of organisational harnessing through linkages to strategy and performance are noted and advocacy is offered for the development of appropriate learning cultures linked to communities of practice that bring specialists together from across regional project societies. Research limitations/implications: The socio-political context of the EEDSM programme, although briefly addressed for its organisational cultural implications, was not given detailed consideration in the exploratory interviews. This would have enhanced the idiographic complexity of the findings, while also reducing prospects for distilling generalisable organisational learning improvement opportunities for emerging project societies. However, the study does not seek to provide evidence for specific learning practice effects on performance as this was not something the interviewees felt able to comment on in significant detail. Originality/value: Learning practice studies for small- and medium-sized project organisations remains sparse, so are studies of business environments within developing countries, in general, or sub-Saharan Africa, in particular. Looking beyond narrow individual project views of performance, the present study's project society-based business environment is theorised as both constraining and benefiting from the project-learning practices discussed by the respondents.

Management Research Review

Organisational learning in small and medium sized South African energy project organisations

The study investigates the performance of Cu2+ as dissolved cathodic electron-shuttle mediator (dcESM) for simultaneous Cr6+ reduction and electricity generation in a microbial fuel cell (MFC) at pH 2 and 4 conditions. The dcESM behavior of Cu2+ on carbon cloth (CC) catalyzes the reduction of Cr6+ into Cr3+ at pH 2 by undergoing redox reactions. However, at pH 4, a simultaneous reduction of Cu2+ and Cr6+ was observed. Cyclic voltammetry studies were performed at pH 2 and 4 to probe the dcESM behavior of Cu2+ for Cr6+ reduction on CC electrode. Also, at pH 2, increasing the concentration of Cu2+ from 50 to 500 mg L- 1 favors the Cr6+ reduction by reducing the reaction time from 108 to 48 h and improving the current production from 3.9 to 6.2 mA m- 2, respectively. Nevertheless, at pH 4, the efficacy of Cr6+ reduction and electricity generation from MFC is decreased from 63 to 18% and 4.4 to 1.1 mA m- 2, respectively, by increasing the Cu2+ concentration from 50 to 500 mg L- 1. Furthermore, the performance of dcESM behavior of Cu2+ was explored on carbon felt (CF) and platinum (Pt) electrodes, and compare the results with CC. In MFC, at pH 2, with an initial concentration of 100 mg L- 1, the reduction of Cr6+ in 60 h is 9.6 mg L- 1 for CC, 0.2 mg L- 1 for CF, and 51.3 mg L- 1 for Pt cathodes. The reduction of Cr6+ (initial concentration of 100 mg L- 1) at pH 4 in 120 h is 44.7 mg L- 1 for CC, 32.1 mg L- 1 for CF, and 70.9 mg L- 1 for Pt cathodes. Maximum power densities of 1659, 1509, and 1284 mW m- 2 were achieved when CF, CC, and Pt, respectively were employed as cathodes in the MFC. © 2020 The Author(s).

Fulltext

Sustainable Environment Research

The performance of Cu2+as dissolved cathodic electron-shuttle mediator for Cr6+reduction in the microbial fuel cell

Discontinuous Galerkin (DG) methods have become mainstays in the accurate solution of hyperbolic systems, which suggests that they should also be important for computational electrodynamics (CED). Typically DG schemes are coupled with Runge-Kutta timestepping, resulting in RKDG schemes, which are also sometimes called DGTD schemes in the CED community. However, Maxwell's equations, which are solved in CED codes, have global mimetic constraints. In Balsara and Käppeli [von Neumann Stability Analysis of Globally Constraint-Preserving DGTD and PNPM Schemes for the Maxwell Equations using Multidimensional Riemann Solvers, Journal of Computational Physics, 376 (2019) 1108-1137] the authors presented globally constraint-preserving DGTD schemes for CED. The resulting schemes had excellent low dissipation and low dispersion properties. Their one deficiency was that the maximal permissible CFL of DGTD schemes decreased with increasing order of accuracy. The goal of this paper is to show how this deficiency is overcome. Because CED entails the propagation of electromagnetic waves, we would also like to obtain DG schemes for CED that minimize dissipation and dispersion errors even more than the prior generation of DGTD schemes. Two recent advances make this possible. The first advance, which has been reported elsewhere, is the development of a multidimensional Generalized Riemann Problem (GRP) solver. The second advance relates to the use of Two Derivative Runge Kutta (TDRK) timestepping. This timestepping uses not just the solution of the multidimensional Riemann problem, it also uses the solution of the multidimensional GRP. When these two advances are melded together, we arrive at DG(TD)2 schemes for CED, where the first “TD” stands for time-derivative and the second “TD” stands for the TDRK timestepping. The first goal of this paper is to show how DG(TD)2 schemes for CED can be formulated with the help of the multidimensional GRP and TDRK timestepping. The second goal of this paper is to utilize the free parameters in TDRK timestepping to arrive at DG(TD)2 schemes for CED that offer a uniformly large CFL with increasing order of accuracy while minimizing the dissipation and dispersion errors to exceptionally low values. The third goal of this paper is to document a von Neumann stability analysis of DG(TD)2 schemes so that their dissipation and dispersion properties can be quantified and studied in detail. At second order we find a DG(TD)2 scheme with CFL of 0.25 and improved dissipation and dispersion properties; for a second order scheme. At third order we present a novel DG(TD)2 scheme with CFL of 0.2571 and improved dissipation and dispersion properties; for a third order scheme. At fourth order we find a DG(TD)2 scheme with CFL of 0.2322 and improved dissipation and dispersion properties. As an extra benefit, the resulting DG(TD)2 schemes for CED require fewer synchronization steps on parallel supercomputers than comparable DGTD schemes for CED. We also document some test problems to show that the methods achieve their design accuracy. © 2020 Elsevier Inc.

Department of Mechanical Engineering

Journal of Computational Physics

Optimal, globally constraint-preserving, DG(TD)2 schemes for computational electrodynamics based on two-derivative Runge-Kutta timestepping and multidimensional generalized Riemann problem solvers – A von Neumann stability analysis

The static deployment of Virtualized Network Functions (VNFs) introduces 1) significant degradation of Quality of Service (QoS), 2) inefficiency in the network and computing resource utilization, and 3) Network Function Virtualization (NFV)-based services with insufficient scalability, optimality, and flexibility. Caching VNFs is a promising solution to satisfy the dynamic demand to deploy a variety of VNFs and to maximize the performance as well as cost effectiveness. Although the concept of Content Delivery Network (CDN) is popular for efficiently caching and distributing contents, VNF deployment does not realize the benefit of CDN-based caching approaches. The challenges to caching VNFs are 1) to cover the large variety of VNFs and their properties, including the necessity of service chaining, and 2) to achieve high acceptance ratio given the limited availability of resources. This paper proposes Function Delivery Network (FDN), which is a cluster of distributed edge hypervisors for caching VNFs over a Software-Defined Network (SDN). The deployment and quality of the network function can be significantly improved by serving them closer to the end-users from the cached VNFs. FDN introduces a new strategy called Value-based caching that considers 1) the locality of reference and performance parameters of network and edge hypervisors together and 2) a partial deployment of service chains across multiple edge hypervisors for further efficient utilization of hypervisors resources. Evaluations on different patterns of input requests confirm thatValue-based caching introduces significant improvement on both QoS and resource utilization in NFV. © 2020 Institute of Electronics, Information and Communication, Engineers, IEICE. All rights reserved.

IEICE Transactions on Communications

FDN: Function delivery network-optimizing service chain deployment in nfv

We study the spreading of viruses, such as SARS-CoV-2, by airborne aerosols, via a first-passage-time problem for Lagrangian tracers that are advected by a turbulent flow: By direct numerical simulations of the three-dimensional (3D) incompressible Navier-Stokes equation, we obtain the time tR at which a tracer, initially at the origin of a sphere of radius R, crosses the surface of the sphere for the first time. We obtain the probability distribution function P(R,tR) and show that it displays two qualitatively different behaviors: (a) for Râ‰LI, P(R,tR) has a power-law tail ∼tR-α, with the exponent α=4 and LI the integral scale of the turbulent flow; (b) for LIâ‰²R, the tail of P(R,tR) decays exponentially. We develop models that allow us to obtain these asymptotic behaviors analytically. We show how to use P(R,tR) to develop social-distancing guidelines for the mitigation of the spreading of airborne aerosols with viruses such as SARS-CoV-2. © 2020 authors. Published by the American Physical Society.