1,720,957 research outputs found
Improving Quality of Results for High-Level Synthesis based FPGA designs
No full textL'abstract è presente nell'allegato / the abstract is in the attachmen
Array-specific dataflow caches for high-level synthesis of memory-intensive algorithms on FPGAs
Full text linkDesigns implemented on field-programmable gate arrays (FPGAs) via high-level synthesis
(HLS) suffer from off-chip memory latency and bandwidth bottlenecks. FPGAs can access both large but slow off-chip memories (DRAM), and fast but small on-chip memories (block RAMs and registers). HLS tools allow exploiting the memory hierarchy in a scratchpad-like fashion, requring a significant manual effort. We propose an automation of the FPGA memory management in Xilinx Vitis HLS through a fully- configurable C++ source-level cache. Each DRAM-mapped array can be associated with a private level 2 (L2) cache with one or more ports, and each port can optionally provide level 1 cache. The L2 cache runs in a separate dataflow task with respect to the application accessing it. This solution isolates off-chip
memory accesses and data buffering into dedicated dataflow tasks, resembling the load, compute, store design paradigm, but without the drawback of manual algorithm refactoring. Experimental results collected from FPGA board show that our cache speeds up the execution of a variety of benchmarks by up to 60 times compared to the out-of-the-box solution provided by HLS, requiring very limited optimization effort. Our caches are not meant to compete with manually optimized implementations quality of results (QoR), but rather to significantly save design effort, in exchange for some QoR, to make the HLS flow a bit more software-like, allowing the designer to focus on algorithmic optimizations, rather than on explicit memory
management. Moreover, caching could be the only feasible memory optimization for algorithms with data-dependent or irregular memory access patterns, but with good data locality
A Graph Neural Network Model for Fast and Accurate Quality of Result Estimation for High-Level Synthesis
Full text linkHigh-level synthesis (HLS) is a solution for rapid prototyping of application-specific hardware
using the C/C++ behavioral programming language. Designers can apply HLS directives to optimize hardware
implementations by making tradeoffs between cost and performance. However, current HLS tools do not
provide reliable quality of results (QoR) estimates, which prevents designers from making these tradeoffs
efficiently to ensure that the design meets the constraints. Taking advantage of the widespread use of machine
learning (ML) to improve the predictability of electronic design automation (EDA) tools, we propose several
graph neural network (GNN)-based models that learn and predict the post-implementation QoR from the
pre-schedule control data flow graph (CDFG) representation of an HLS design targeting field-programmable
gate array (FPGA) implementation, considering also the user HLS optimization directives. Experimental
results show that our model can estimate the timing and resource usage of a previously unseen design (i.e, a
completely new CDFG) within milliseconds with high accuracy, reducing prediction errors by up to 74%
compared to the estimate generated by the HLS tool itself after going through time-consuming scheduling
and binding, and by 29% and 22% for resource usage and timing prediction, respectively, compared to the
state-of-the-art
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
LESS: Low-Power Energy-Efficient Subgraph Isomorphism on FPGA
Full text linkLow-power energy-efflcient subgraph isomorphism (LESS) is an open-source field-programmable gate array-only low-memory sub graph matching solver designed for energy efficiency. Depending on the input datagraph, the energy consumption of LESS, averaged on different diverse queries, is up to 38x and 93x lower than CPU and GPU solvers respectively
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
- …
