Aalap Tripathy

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This paper covers the use of depth sensors such as Microsoft Kinect and ASUS Xtion to provide a natural user interface (NUI) for controlling 3-D (three-dimensional) virtual globes such as Google Earth (including its Street View mode), Bing Maps 3D, and NASA World Wind. The paper introduces the Microsoft Kinect device, briefly describing how it works (the(More)
To enable meaning based search, computers have to store and compare meaning of user’s search intentions and objects being searched. To address the key requirement of meaning compositionality, we present: design rationale; an algebraic theory; and a technique to represent composite meaning as a tensor which is amenable to efficient similarity(More)
The increasing amount of information accessible to a user digitally makes information retrieval & filtering difficult, time consuming and ineffective. New meaning representation techniques proposed in literature help to improve accuracy but increase problem size exponentially. In this paper, we present a novel reconfigurable computing architecture that(More)
Superior and fast semantic comparison improves the quality of web-search. Semantic comparison involves dot product computation of large sparse tensors which is time consuming and expensive. In this paper we present a low power parallel architecture that consumes only 15.41 Watts and demonstrates a speed-up in the order of 10textsuperscript{5} compared to a(More)
In this paper we present a fine grained parallel architecture that performs meaning comparison using vector cosine similarity (dot product). Meaning comparison assigns a similarity value to two objects (e.g. text documents) based on how similar their meanings (represented as two vectors) are to each other. The novelty of our design is the fine grained(More)
Emerging semantic search techniques require fast comparison of large "concept trees". This paper addresses the challenges involved in fast computation of similarity between two large concept trees using a CUDA-enabled GPGPU co-processor. We propose efficient techniques for the same using fast hash computations, membership tests using Bloom Filters and(More)
The web is moving from an era of "search" to that of "discovery". Collaborative filtering (CF) recommender systems are now commonly used to predict user's preference towards an unknown item from past ratings. To be scalable or effective, they are typically deployed in distributed clusters and operate on extremely large apriori datasets. Improvement of the(More)
Fast response requirements for big-data applications on cloud infrastructures continues to grow. At the same time, many cores on-chip have now become a reality. These developments are set to redefine infrastructure nodes of cloud data centers in the future. For this to happen, parallel programming runtimes need to be designed for many-cores on chip as the(More)
Many-cores on chip have now become a reality. They necessitate the revisit of several layers of a cloud infrastructure. For this to happen, parallel programming runtimes need to be designed for many-cores on chip as the target architecture. In this paper, we show that Map Reduce programming paradigm can be adapted to run on Intel's experimental single chip(More)
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