Minimizing Flow-Time on Unrelated Machines

We consider some flow-time minimization problems in the unrelated machines setting. In this setting, there is a set of $m$ machines and a set of $n$ jobs, and each job $j$ has a machine dependent processing time of $p_{ij}$ on machine $i$. The flow-time of a job is the total time the job spends in the system (completion time minus its arrival time), and is one of the most natural quality of service measure. We show the following two results: an $O(\min(\log^2 n,\log n \log P))$ approximation algorithm for minimizing the total-flow time, and an $O(\log n)$ approximation for minimizing the maximum flow-time. Here $P$ is the ratio of maximum to minimum job size. These are the first known poly-logarithmic guarantees for both the problems.Comment: The new version fixes some typos in the previous version. The paper is accepted for publication in STOC 201

Design and development of manufacturing methods for manufacturing of PEM fuel cell MEA\u27s

This thesis focuses on design and manufacturing of Fuel cell components using Additive Manufacturing techniques and then in the later part on design and manufacturing of Membrane Electrode Assembly (MEA) which is a very important component in fuel cells. Additive manufacturing methods are fast and efficient manufacturing methods which are additive building up components layer by layer instead of conventional subtractive manufacturing techniques. This ensures low cost and faster manufacturing. Additive manufacturing is important for fuel cell component manufacturing since it is important in fuel cells to minimize wastage and reduce the cost. MEA is the basis of the cost factor in Proton Exchange Membrane (PEM) fuel cells. It contributes for more than 50% of the cost in a fuel cell. In order to reduce the cost of a fuel cell/kW, it is necessary to achieve the maximum performance of the fuel cell using least amount of the platinum catalyst. The best way to achieve that is to achieve a uniform loading of the catalyst through the entire area of the MEA. Along with this, it is important to have an efficient and at the same time a fast manufacturing method for MEA\u27s. This thesis discusses two methods, namely Direct Deposition Process (DDP) and Electro-Write Process (EWP) and compares the efficiencies of the two using a novel way employing Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) techniques. This thesis also focuses on the importance of cost model and efficiency measurement techniques for monitoring a manufacturing method in order to know the impact of every manufacturing method of individual components on the total cost of the product --Abstract, page iv

Truth and Regret in Online Scheduling

We consider a scheduling problem where a cloud service provider has multiple units of a resource available over time. Selfish clients submit jobs, each with an arrival time, deadline, length, and value. The service provider's goal is to implement a truthful online mechanism for scheduling jobs so as to maximize the social welfare of the schedule. Recent work shows that under a stochastic assumption on job arrivals, there is a single-parameter family of mechanisms that achieves near-optimal social welfare. We show that given any such family of near-optimal online mechanisms, there exists an online mechanism that in the worst case performs nearly as well as the best of the given mechanisms. Our mechanism is truthful whenever the mechanisms in the given family are truthful and prompt, and achieves optimal (within constant factors) regret. We model the problem of competing against a family of online scheduling mechanisms as one of learning from expert advice. A primary challenge is that any scheduling decisions we make affect not only the payoff at the current step, but also the resource availability and payoffs in future steps. Furthermore, switching from one algorithm (a.k.a. expert) to another in an online fashion is challenging both because it requires synchronization with the state of the latter algorithm as well as because it affects the incentive structure of the algorithms. We further show how to adapt our algorithm to a non-clairvoyant setting where job lengths are unknown until jobs are run to completion. Once again, in this setting, we obtain truthfulness along with asymptotically optimal regret (within poly-logarithmic factors)

D2P: Automatically Creating Distributed Dynamic Programming Codes

Dynamic Programming (DP) algorithms are common targets for parallelization, and, as these algorithms are applied to larger inputs, distributed implementations become necessary. However, creating distributed-memory solutions involves the challenges of task creation, program and data partitioning, communication optimization, and task scheduling. In this paper we present D2P, an end-to-end system for automatically transforming a specification of any recursive DP algorithm into distributed-memory implementation of the algorithm. When given a pseudo-code of a recursive DP algorithm, D2P automatically generates the corresponding MPI-based implementation. Our evaluation of the generated distributed implementations shows that they are efficient and scalable. Moreover, D2P-generated implementations are faster than implementations generated by recent general distributed DP frameworks, and are competitive with (and often faster than) hand-written implementations

Abundance of Secondary Metabolites in Human Microbiome

Digitized for IUPUI ScholarWorks inclusion in 2021.Human body harbors the most complicated microbial ecosystem. Bacteria that have co-evolved within a human context have barely been explored for secondary metabolites. These secondary metabolites are hypothesized to possess biological activities significant within the human host context. In our study, we studied conservation profiles of 203 secondary metabolite gene clusters across 16 human body sites and found that gastrointestinal tract and oral sites show the highest conservation for secondary metabolic gene clusters. We observed that majority of highly conserved metabolites belong to pathway type NRPS. Our phylogenetic analysis of highly conserved stool and oral samples revealed abundance of firmicutes, bacteroidetes and actinobacteria phylum

Graph Properties in Node-Query Setting: Effect of Breaking Symmetry

The query complexity of graph properties is well-studied when queries are on the edges. We investigate the same when queries are on the nodes. In this setting a graph G = (V,E) on n vertices and a property P are given. A black-box access to an unknown subset S of V is provided via queries of the form "Does i belong to S?". We are interested in the minimum number of queries needed in the worst case in order to determine whether G[S] - the subgraph of G induced on S - satisfies P. Our primary motivation to study this model comes from the fact that it allows us to initiate a systematic study of breaking symmetry in the context of query complexity of graph properties. In particular, we focus on the hereditary graph properties - properties that are closed under deletion of vertices as well as edges. The famous Evasiveness Conjecture asserts that even with a minimal symmetry assumption on G, namely that of vertex-transitivity, the query complexity for any hereditary graph property in our setting is the worst possible, i.e., n. We show that in the absence of any symmetry on G it can fall as low as O(n^{1/(d + 1)}) where d denotes the minimum possible degree of a minimal forbidden sub-graph for P. In particular, every hereditary property benefits at least quadratically. The main question left open is: Can it go exponentially low for some hereditary property? We show that the answer is no for any hereditary property with finitely many forbidden subgraphs by exhibiting a bound of Omega(n^{1/k}) for a constant k depending only on the property. For general ones we rule out the possibility of the query complexity falling down to constant by showing Omega(log(n)*log(log(n))) bound. Interestingly, our lower bound proofs rely on the famous Sunflower Lemma due to Erdos and Rado

STT-MRAM Based NoC Buffer Design

As Chip Multiprocessor (CMP) design moves toward many-core architectures, communication delay in Network-on-Chip (NoC) is a major bottleneck in CMP design. An emerging non-volatile memory - STT MRAM (Spin-Torque Transfer Magnetic RAM) which provides substantial power and area savings, near zero leakage power, and displays higher memory density compared to conventional SRAM. But STT-MRAM suffers from inherit drawbacks like multi cycle write latency and high write power consumption. So, these problem have to addressed in order to have an efficient design to incorporate STT-MRAM for NoC input buffer instead of traditional SRAM based input buffer design. Motivated by short intra-router latency, previously proposed write latency reduction technique is explored by sacrificing retention time and a hybrid design of input buffers using both SRAM and STT-MRAM to "hide" the long write latency efficiently is proposed. Considering that simple data migration in the hybrid buffer consumes more dynamic power compared to SRAM, a lazy migration scheme that reduces the dynamic power consumption of the hybrid buffer is also proposed

Pseudospectral Shattering, the Sign Function, and Diagonalization in Nearly Matrix Multiplication Time

We exhibit a randomized algorithm which given a square $n\times n$ complex matrix $A$ with $\|A\| \le 1$ and $\delta>0$, computes with high probability invertible $V$ and diagonal $D$ such that $$\|A-VDV^{-1}\|\le \delta$$ and $\|V\|\|V^{-1}\| \le O(n^{2.5}/\delta)$ in $O(T_{MM}\>(n)\log^2(n/\delta))$ arithmetic operations on a floating point machine with $O(\log^4(n/\delta)\log n)$ bits of precision. Here $T_{MM}\>(n)$ is the number of arithmetic operations required to multiply two $n\times n$ complex matrices numerically stably, with $T_{MM}\,\,(n)=O(n^{\omega+\eta}\>\>)$ for every $\eta>0$, where $\omega$ is the exponent of matrix multiplication. The algorithm is a variant of the spectral bisection algorithm in numerical linear algebra (Beavers and Denman, 1974). This running time is optimal up to polylogarithmic factors, in the sense that verifying that a given similarity diagonalizes a matrix requires at least matrix multiplication time. It significantly improves best previously provable running times of $O(n^{10}/\delta^2)$ arithmetic operations for diagonalization of general matrices (Armentano et al., 2018), and (w.r.t. dependence on $n$) $O(n^3)$ arithmetic operations for Hermitian matrices (Parlett, 1998). The proof rests on two new ingredients. (1) We show that adding a small complex Gaussian perturbation to any matrix splits its pseudospectrum into $n$ small well-separated components. This implies that the eigenvalues of the perturbation have a large minimum gap, a property of independent interest in random matrix theory. (2) We rigorously analyze Roberts' Newton iteration method for computing the matrix sign function in finite arithmetic, itself an open problem in numerical analysis since at least 1986. This is achieved by controlling the evolution the iterates' pseudospectra using a carefully chosen sequence of shrinking contour integrals in the complex plane.Comment: 78 pages, 3 figures, comments welcome. Slightly edited intro from previous version + explicit statement of forward error Theorem (Corolary 1.7). Minor corrections mad

Awareness and Perception of Plastic Surgery among Healthcare Professionals in Pune, India: Do They Really Know What We Do?

Purpose. The aim of this study is to understand the level of awareness and knowledge of plastic surgery in healthcare professionals in a tertiary health care facility in Pune, India. This study also aims to highlight the perception of the medical professionals about plastic surgery and what they think a plastic surgeon does. Materials and Methods. A questionnaire-based survey was done at B.J Medical College and Sassoon Hospital, Pune in 2011. Feedback evaluation forms from hundred resident doctors and faculty were evaluated and analyzed. Results. There is not much awareness about plastic surgery as a specialty amongst health care providers. Plastic surgery is mostly perceived as cosmetic surgery, and the other spectrum of the patients we cater to goes largely unnoticed. Of all the clinical conditions given to the participants, there was not a single clinical condition where the respondents favored unanimously for plastic surgeons. Conclusion. Plastic surgery as a specialty is poorly understood by our medical colleagues, and the onus of creating and improving the awareness and perception of our specialty lies on us. Herculean unified efforts at individual as well as global level will help us achieve this goal