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Eli Koffi Kouassi, Toshiyuki Amagasaa, Hiroyuki Kitagawa
In this paper, we propose a scheme to accelerate the Probabilistic Latent Semantic Indexing (PLSI), which is an automated document indexing method based on a statistical latent semantic model, exploiting the high parallelism of Graphics Processing Unit (GPU). Our proposal is composed of three techniques: the first one is to accelerate the Expectation-Maximization (EM) computation […]
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Aalap Tripathy, Suneil Mohan, Rabi Mahapatra
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 parallel reduction. We show how a […]
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Abhinandan Majumdar, Srihari Cadambi, Srimat T. Chakradhar, Hans Peter Graf
Semantic text analysis is a technique used in advertisement placement, cognitive databases and search engines. With increasing amounts of data and stringent response-time requirements, improving the underlying implementation of semantic analysis becomes critical. To this end, we look at Supervised Semantic Indexing (SSI), a recently proposed algorithm for semantic analysis. SSI ranks a large number […]
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Surendra Byna,Jiayuan Meng,Anand Raghunathan,Srimat Chakradhar,Srihari Cadambi
Semantic indexing is a popular technique used to access and organize large amounts of unstructured text data. We describe an optimized implementation of semantic indexing and document search on manycore GPU platforms. We observed that a parallel implementation of semantic indexing on a 128-core Tesla C870 GPU is only 2.4X faster than a sequential implementation […]

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