The article discusses the results of computer programming language studies conducted by Sun Microsystems in the context of a High Productivity Computing Systems (HPCS) program run by the U.S. Defense Advanced Research...
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The article discusses the results of computer programming language studies conducted by Sun Microsystems in the context of a High Productivity Computing Systems (HPCS) program run by the U.S. Defense Advanced Research Projects Agency (DARPA). The studies attempted to determine what the optimal characteristics of a high-performance computing (HPC) programming language would be. The traditional language, Fortran, was actually found to be surprisingly effective. The main obstacles to well-written programs often involved artifacts introduced by the specific hardware limitations of central processing units, or questionable choices in a program's conceptual design, rather than limitations in the language itself.
This paper describes the design and implementation of a TT Lite certifying supercompiler, which transforms a source program into a pair consisting of a residual program and a proof that the residual program is equival...
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This paper describes the design and implementation of a TT Lite certifying supercompiler, which transforms a source program into a pair consisting of a residual program and a proof that the residual program is equivalent to the source one. As far as we can judge from the presently available literature, it is the first time that certifying supercompilation is implemented for a nontrivial higher-order functional language. Proofs generated by the TT Lite supercompiler can be verified by the type checker that does not depend on the supercompiler and is not based on supercompilation. This is especially important when reliability of results obtained by means of supercompilation is of primary concern.
Motivation: Detecting drug-drug interaction (DDI) has become a vital part of public health safety. Therefore, using text mining techniques to extract DDIs from biomedical literature has received great attentions. Howe...
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Motivation: Detecting drug-drug interaction (DDI) has become a vital part of public health safety. Therefore, using text mining techniques to extract DDIs from biomedical literature has received great attentions. However, this research is still at an early stage and its performance has much room to improve. Results: In this article, we present a syntax convolutional neural network (SCNN) based DDI extraction method. In this method, a novel word embedding, syntax word embedding, is proposed to employ the syntactic information of a sentence. Then the position and part of speech features are introduced to extend the embedding of each word. Later, auto-encoder is introduced to encode the traditional bag-of-words feature (sparse 0-1 vector) as the dense real value vector. Finally, a combination of embedding-based convolutional features and traditional features are fed to the softmax classifier to extract DDIs from biomedical literature. Experimental results on the DDIExtraction 2013 corpus show that SCNN obtains a better performance (an F-score of 0.686) than other state-of-the-art methods.
A survey found the language in use in introductory programming classes in the top U.S. computer science *** MATERIALS AVAILABLE FOR DOWNLOADHtml(18KB) PDF(137KB) Digital Edition
A survey found the language in use in introductory programming classes in the top U.S. computer science *** MATERIALS AVAILABLE FOR DOWNLOADHtml(18KB) PDF(137KB) Digital Edition
Motivation: Extracting biological insight from genomic data inevitably requires custom software. In many cases, this is accomplished with scripting languages, owing to their accessibility and brevity. Unfortunately, t...
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Motivation: Extracting biological insight from genomic data inevitably requires custom software. In many cases, this is accomplished with scripting languages, owing to their accessibility and brevity. Unfortunately, the ease of scripting languages typically comes at a substantial performance cost that is especially acute with the scale of modern genomics datasets. Results: We present hts-nim, a high-performance library written in the Nim programming language that provides a simple, scripting-like syntax without sacrificing performance. Availability and implementation: hts-nim is available at https://github. com/brentp/hts-nim and the example tools are at https://github. com/brentp/hts-nim-tools both under the MIT license.
Motivation: With the rapid development of Next-Generation Sequencing, a large amount of data is now available for bioinformatics research. Meanwhile, the presence of many pipeline frameworks makes it possible to analy...
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Motivation: With the rapid development of Next-Generation Sequencing, a large amount of data is now available for bioinformatics research. Meanwhile, the presence of many pipeline frameworks makes it possible to analyse these data. However, these tools concentrate mainly on their syntax and design paradigms, and dispatch jobs based on users' experience about the resources needed by the execution of a certain step in a protocol. As a result, it is difficult for these tools to maximize the potential of computing resources, and avoid errors caused by overload, such as memory overflow. Results: Here, we have developed BioQueue, a web-based framework that contains a checkpoint before each step to automatically estimate the system resources (CPU, memory and disk) needed by the step and then dispatch jobs accordingly. BioQueue possesses a shell command-like syntax instead of implementing a new script language, which means most biologists without computer programming background can access the efficient queue system with ease.
A Summary: Simulation programs based on the coalescent efficiently generate genetic data according to a given model of evolution. We present coala, an R package for calling coalescent simulators with a unified syntax....
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A Summary: Simulation programs based on the coalescent efficiently generate genetic data according to a given model of evolution. We present coala, an R package for calling coalescent simulators with a unified syntax. It can execute simulations with several programs, calculate additional summary statistics and combine multiple simulations to create biologically more realistic data.
In this article, I propose a unified explanation for the argument-adjunct asymmetries that have been observed regarding two seemingly unrelated anti-c-command requirements: (i) condition C and (ii) the anti-c-command ...
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In this article, I propose a unified explanation for the argument-adjunct asymmetries that have been observed regarding two seemingly unrelated anti-c-command requirements: (i) condition C and (ii) the anti-c-command requirement on argument ellipsis, observed in Abe 2009 for null arguments in Japanese. I argue that these asymmetries are best explained by the mechanism of late merge of adjuncts proposed by Lebeaux (1988) with a derivational definition of c-command a la Epstein (1999). Furthermore, I argue that the timing of late merge of adjuncts is regulated by phase theory in the way that adjuncts may be merged no later than completion of relevant operations at the phase domains they belong to.
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