Topics
high-performance computingInformation appliance
The demands placed on systems to analyse corpus data increase with input size, and the traditional approaches to processing this data are increasingly having impractical run-times. We show that the use of desktop GPUs presents a significant opportunity to accelerate a number of stages in the normal corpus analysis pipeline. This paper contains our exploratory work and findings into applying high-performance computing technology and methods to the problem of sorting large numbers of concordance lines
AbstractIn this paper, we show how to employ Graphics Processing Units (GPUs) to provide an effcient...
At the International Research Workshop on Advanced High Performance Computing Systems held in Cetrar...
Probabilistic Latent Semantic Analysis (PLSA) has been successfully applied to many text mining task...
The demands placed on systems to analyse corpus data increase with input size, and the traditional a...
Algorithms for processing large, unstructured data sets have shown great promise in implementations ...
Abstract—The current generation of Graphics Processing Units (GPUs) contain a large number of genera...
Big data analytics is eventual discovery of knowledge from large set of data thus leading to busines...
Sorting is an important problem in computing that has a rich history of investigation by various res...
Although sort has been extensively studied in many research works, it still remains a challenge in p...
Latent Semantic Analysis (LSA) aims to reduce the dimensions of large term-document datasets using S...
Data analysis is a rising field of interest for computer science research due to the growing amount ...
Big Data applications are trivially parallelizable because they typically consist of simple and stra...
Big data processing relies today on complex middleware stacks, comprised of high-level languages, pr...
In this paper, we show how to employ Graphics Processing Units (GPUs) to provide an effcient and hig...
The general-purpose computing capabilities of the Graphics Processing Unit (GPU) have recently been ...
AbstractIn this paper, we show how to employ Graphics Processing Units (GPUs) to provide an effcient...
At the International Research Workshop on Advanced High Performance Computing Systems held in Cetrar...
Probabilistic Latent Semantic Analysis (PLSA) has been successfully applied to many text mining task...
The demands placed on systems to analyse corpus data increase with input size, and the traditional a...
Algorithms for processing large, unstructured data sets have shown great promise in implementations ...
Abstract—The current generation of Graphics Processing Units (GPUs) contain a large number of genera...
Big data analytics is eventual discovery of knowledge from large set of data thus leading to busines...
Sorting is an important problem in computing that has a rich history of investigation by various res...
Although sort has been extensively studied in many research works, it still remains a challenge in p...
Latent Semantic Analysis (LSA) aims to reduce the dimensions of large term-document datasets using S...
Data analysis is a rising field of interest for computer science research due to the growing amount ...
Big Data applications are trivially parallelizable because they typically consist of simple and stra...
Big data processing relies today on complex middleware stacks, comprised of high-level languages, pr...
In this paper, we show how to employ Graphics Processing Units (GPUs) to provide an effcient and hig...
The general-purpose computing capabilities of the Graphics Processing Unit (GPU) have recently been ...
AbstractIn this paper, we show how to employ Graphics Processing Units (GPUs) to provide an effcient...
At the International Research Workshop on Advanced High Performance Computing Systems held in Cetrar...
Probabilistic Latent Semantic Analysis (PLSA) has been successfully applied to many text mining task...
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