1,720,963 research outputs found
A Data-Flow Soft-Core Processor for Accelerating Scientific Calculation on FPGAs
Full text linkWe present a new type of soft-core processor called the “Data-Flow Soft-Core” that can be implemented through FPGA technology with adequate interconnect resources. This processor provides data processing based on data-flow instructions rather than control flow instructions. As a result, during an execution on the accelerator of the Data-Flow Soft-Core, both partial data and instructions are eliminated as traffic for load and store activities. Data-flow instructions serve to describe a program and to dynamically change the context of a data-flow program graph inside the accelerator, on-the-fly. Our proposed design aims at combining the performance of a fine-grained data-flow architecture with the flexibility of reconfiguration, without requiring a partial reconfiguration or new bit-stream for reprogramming it. The potential of the data-flow implementation of a function or functional program can be exploited simply by relying on its description through the data-flow instructions that reprogram the Data-Flow Soft-Core. Moreover, the data streaming process will mirror those present in other FPGA applications. Finally, we show the advantages of this approach by presenting two test cases and providing the quantitative and numerical results of our evaluations
A matrix multiplier case study for an evaluation of a configurable Dataflow-Machine
No full textConfigurable computing has become a subject of a great deal of research given its potential to greatly accelerate a wide variety of applications that require high throughput. In this context, the dataflow approach is still promising to accelerate the kernel of applications in the field of HPC. That tanks to a computational dataflow engine able to execute dataflow program graphs directly in a custom hardware. On the other hand, evaluating radically different models of computation remains yet an open issue. In this paper we present as case study the matrix multiplication that constitutes the fundamental kernel of the linear algebra. The evaluation takes into account the execution of the matrix product both in non-pipelined and pipelined modes. Results obtained running the execution of the two modes on an FPGA-based demonstrator show the validity of the configurable Dataflow-Machine. Moreover, at the same throughput, the power consumption is expected to be lower than in clock-based systems
A Data-Flow Methodology for Accelerating FFT
No full textThe native implementation of the N-point digital Fourier Transform involves calculating the scalar product of the sample buffer (treated as an N-dimensional vector) with N separate basis vectors. Since each scalar product involves N multiplications and N additions, the total time is proportional to N-2, in other words, its an O(N-2) algorithm. However, it turns out that by cleverly re-arranging these operations, one can optimize the algorithm down to O(Nlog(2)(N)), which for large N makes a huge difference. The optimized version of the algorithm is called the Fast Fourier Transform, or the FFT.In this paper, we discuss about an efficient way to obtain Fast Fourier Transform algorithm (FFT). According to our study, we can eliminate some operations in calculating the FFT algorithm thanks to property of complex numbers and we can achieve the FFT in a better execution time due to a significant reduction of N/8 of the needed twiddle factors and to additional factorizations
A Clockless Computing System based on the Static Dataflow Paradigm
No full textThe ambitious challenges posed by next exascale computing systems may require a critical re-examination of both architecture design and consolidated wisdom in terms of programming style and execution model, because such systems are expected to be constituted by thousands of processors with thousands of cores per chip. But how to build exascale architectures remains an open question. This paper presents a novel computing system based on a configurable architecture and a static dataflow execution model. We assume that the basic computational unit is constituted by a dataflow graph. Each processing node is constituted by an ad hoc kernel processor - designed to manage and schedule dataflow graphs, and a manycore dataflow execution engine - designed to execute such dataflow graphs. The main components of the dataflow execution engine are the Dataflow Actor Cores (DACs), which are small, identical and configurable. The major contributions of this paper are: i) the introduction of a machine language (named D#) which represents the low-level static configuration information of the system; ii) the introduction of a self-scheduled clockless mechanism to start operations on the presence of validity tokens only; iii) a design that avoids the need of temporary storage for tokens on the links of the DACs. Our preliminary tests on FPGA-based hardware show the feasibility of this approach
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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