1,819 research outputs found
OPTIMAL AREA AND PERFORMANCE MAPPING OF K-LUT BASED FPGAS
FPGA circuits are increasingly used in many fields: for rapid prototyping of new products (including fast ASIC implementation), for logic emulation, for producing a small number of a device, or if a device should be reconfigurable in use (reconfigurable computing). Determining if an arbitrary, given wide, function can be implemented by a programmable logic block, unfortunately, it is generally, a very difficult problem. This problem is called the Boolean matching problem. This paper introduces a new implemented algorithm able to map, both for area and performance, combinational networks using k-LUT based FPGAs.k-LUT based FPGAs, combinational circuits, performance-driven mapping.
A system for routing arbitrary directed graphs on SIMD architectures
There are many problems which can be described in terms of directed graphs that contain a large number of vertices where simple computations occur using data from connecting vertices. A method is given for parallelizing such problems on an SIMD machine model that is bit-serial and uses only nearest neighbor connections for communication. Each vertex of the graph will be assigned to a processor in the machine. Algorithms are given that will be used to implement movement of data along the arcs of the graph. This architecture and algorithms define a system that is relatively simple to build and can do graph processing. All arcs can be transversed in parallel in time O(T), where T is empirically proportional to the diameter of the interconnection network times the average degree of the graph. Modifying or adding a new arc takes the same time as parallel traversal
Nature-Inspired Interconnects for Self-Assembled Large-Scale Network-on-Chip Designs
Future nano-scale electronics built up from an Avogadro number of components
needs efficient, highly scalable, and robust means of communication in order to
be competitive with traditional silicon approaches. In recent years, the
Networks-on-Chip (NoC) paradigm emerged as a promising solution to interconnect
challenges in silicon-based electronics. Current NoC architectures are either
highly regular or fully customized, both of which represent implausible
assumptions for emerging bottom-up self-assembled molecular electronics that
are generally assumed to have a high degree of irregularity and imperfection.
Here, we pragmatically and experimentally investigate important design
trade-offs and properties of an irregular, abstract, yet physically plausible
3D small-world interconnect fabric that is inspired by modern network-on-chip
paradigms. We vary the framework's key parameters, such as the connectivity,
the number of switch nodes, the distribution of long- versus short-range
connections, and measure the network's relevant communication characteristics.
We further explore the robustness against link failures and the ability and
efficiency to solve a simple toy problem, the synchronization task. The results
confirm that (1) computation in irregular assemblies is a promising and
disruptive computing paradigm for self-assembled nano-scale electronics and (2)
that 3D small-world interconnect fabrics with a power-law decaying distribution
of shortcut lengths are physically plausible and have major advantages over
local 2D and 3D regular topologies
On the Area of Hypercube Layouts
This paper precisely analyzes the wire density and required area in standard
layout styles for the hypercube. The most natural, regular layout of a
hypercube of N^2 nodes in the plane, in a N x N grid arrangement, uses
floor(2N/3)+1 horizontal wiring tracks for each row of nodes. (The number of
tracks per row can be reduced by 1 with a less regular design.) This paper also
gives a simple formula for the wire density at any cut position and a full
characterization of all places where the wire density is maximized (which does
not occur at the bisection).Comment: 8 pages, 4 figures, LaTe
Division-based versus general decomposition-based multiple-level logic synthesis
During the last decade, many different approaches have been proposed to solve the multiple-level synthesis problem with
different minimum functionally complete systems of primitive logic blocks. The most popular of them is the division-based
approach. However, modem microelectronic technology provides a large variety of building blocks which considerably
differ from those typically considered. The traditional methods are therefore not suitable for synthesis with many modem
building blocks. Furthermore, they often fail to find global optima for complex designs and leave unconsidered some
important design aspects. Some of their weaknesses can be eliminated without leaving the paradigm they are based on, other
ones are more fundamental. A paradigm which enables efficient exploitation of the opportunities created by the
microelectronic technology is the general decomposition paradigm. The aim of this paper is to analyze and compare the
general decomposition approach and the division-based approach. The most important advantages of the general
decomposition approach are its generality (any network of any building blocks can be considered) and totality (all important
design aspects can be considered) as well as handling the incompletely specified functions in a natural way. In many cases,
the general decomposition approach gives much better results than the traditional approaches
Introduction to a system for implementing neural net connections on SIMD architectures
Neural networks have attracted much interest recently, and using parallel architectures to simulate neural networks is a natural and necessary application. The SIMD model of parallel computation is chosen, because systems of this type can be built with large numbers of processing elements. However, such systems are not naturally suited to generalized communication. A method is proposed that allows an implementation of neural network connections on massively parallel SIMD architectures. The key to this system is an algorithm permitting the formation of arbitrary connections between the neurons. A feature is the ability to add new connections quickly. It also has error recovery ability and is robust over a variety of network topologies. Simulations of the general connection system, and its implementation on the Connection Machine, indicate that the time and space requirements are proportional to the product of the average number of connections per neuron and the diameter of the interconnection network
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