By Ramachandran Vaidyanathan
Dynamic Reconfiguration: Architectures and Algorithms bargains a finished therapy of dynamically reconfigurable computing device architectures and algorithms for them. The insurance is wide ranging from primary algorithmic suggestions, ranging throughout algorithms for a wide range of difficulties and functions, to simulations among types. The presentation employs a unmarried reconfigurable version (the reconfigurable mesh) for many algorithms, to allow the reader to distill key rules with out the bulky information of a myriad of types. as well as algorithms, the ebook discusses themes that offer a greater figuring out of dynamic reconfiguration similar to scalability and computational strength, and newer advances corresponding to optical versions, run-time reconfiguration (on FPGA and comparable platforms), and enforcing dynamic reconfiguration. The publication, that includes many examples and a wide set of workouts, is a wonderful textbook or reference for a graduate direction. it's also an invaluable connection with researchers and procedure builders within the zone.
Read or Download Dynamic Reconfiguration Architectures and Algorithms PDF
Similar algorithms books
Algorithms For Interviews (AFI) goals to aid engineers interviewing for software program improvement positions in addition to their interviewers. AFI contains 174 solved set of rules layout difficulties. It covers middle fabric, reminiscent of looking out and sorting; common layout rules, akin to graph modeling and dynamic programming; complex themes, reminiscent of strings, parallelism and intractability.
This publication focuses like a laser beam on one of many most well-liked themes in evolutionary computation during the last decade or so: estimation of distribution algorithms (EDAs). EDAs are a big present method that's resulting in breakthroughs in genetic and evolutionary computation and in optimization extra commonly.
This self-contained monograph is an built-in examine of standard structures outlined by way of iterated family utilizing the 2 paradigms of abstraction and composition. This contains the complexity of a few state-transition platforms and improves knowing of advanced or chaotic phenomena rising in a few dynamical structures.
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: a brand new software for Evolutionary Computation is dedicated to a brand new paradigm for evolutionary computation, named estimation of distribution algorithms (EDAs). This new category of algorithms generalizes genetic algorithms by means of changing the crossover and mutation operators with studying and sampling from the likelihood distribution of the easiest members of the inhabitants at every one generation of the set of rules.
- Digital Fourier Analysis: Fundamentals
- The status of the P versus NP problem
- Algorithms for minimization without derivatives
- Recent Advances in Memetic Algorithms
- High Performance Algorithms and Software for Nonlinear Optimization
- Algorithms in a Nutshell: A Desktop Quick Reference
Additional info for Dynamic Reconfiguration Architectures and Algorithms
Sample text
7. With this ability, we can treat inputs as though they are in adjacent columns of the R-Mesh, a prerequisite for running the algorithm recursively. ) require The Reconfigurable Mesh: A Primer 43 Embedding a distributed sub-R-Mesh is a special case of embedding a graph in the R-Mesh, with each vertex of the graph corresponding to an R-Mesh processor and each edge to a bus between processors emulating vertices. A major drawback of this approach to embedding (mapping vertices to processors and edges to buses) is that the embedded graph must be of degree at most 4.
Modulo Addition of Bits. 3, the bus originating at the W port of processor (0,0) moves to the next row for each 1 in be an integer. 3, each bus the input. Let routes to row 0 on encountering a 1, instead of row in row addition of bits. To implement then the R-Mesh can perform modulo this strategy on the R-Mesh, we will use 2N columns and an additional to row 0. 8 row to allow the bus to fold back from row illustrates this method for a small example. 18). 5 For any the modulo m addition of N bits can be performed on an R-Mesh in O(1) time.
Perform neighbor localization on row 0 to construct list L of active processors in ascending order of their column indices. let point to the next element of For active processor list L. /* Stage 3: Concatenate non-empty lists according to list L. If then this stage constructs a pointer from the last to the first element of */ element of 1. /* This step finds the predecessor, of each element of list L. */ if processor is active then send index to processor using row Processor assigns is active then 2.