Publication

Pattern-based fpga logic block and clustering algorithm

Giovanni De Micheli, Xifan Tang, Pierre-Emmanuel Julien Marc Gaillardon
2016
Patents

Abstract

A routing architecture for fast interconnections between Look-Up Tables (LUTs) in a group of Basic Logic Elements (BLEs), whereby a size of the group ranges from 1 to k+1, where k is the number of inputs of a LUT, and LUTs in the group are indexed from 1 to k+1, and whereby (a) an output of a LUTi, 1≦̸i≦̸k, connects to one of the inputs of routing multiplexers of LUTj, i

Official source

https://infoscience.epfl.ch/entities/publication/4fdbd911-f375-46b9-ae08-2c8d990e856f

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Giovanni De Micheli, Xifan Tang, Pierre-Emmanuel Julien Marc Gaillardon
2016
Patents

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/4fdbd911-f375-46b9-ae08-2c8d990e856f

About this result

Related concepts (22)

Cluster analysis

Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, , information retrieval, bioinformatics, data compression, computer graphics and machine learning.

K-means clustering

k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells. k-means clustering minimizes within-cluster variances (squared Euclidean distances), but not regular Euclidean distances, which would be the more difficult Weber problem: the mean optimizes squared errors, whereas only the geometric median minimizes Euclidean distances.

Sequential logic

In automata theory, sequential logic is a type of logic circuit whose output depends on the present value of its input signals and on the sequence of past inputs, the input history. This is in contrast to combinational logic, whose output is a function of only the present input. That is, sequential logic has state (memory) while combinational logic does not. Sequential logic is used to construct finite-state machines, a basic building block in all digital circuitry.

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