Integration of logic synthesis and high-level synthesis into the DIADES design automation system

Perkowski, Marek; Driscoll, Michael A.; Liu, J.; Smith, Dan; Brown, Jessica E.; Yang, L.; Shamsapour, A.; Helliwell, M.; Falkowski, B.J.; Wu, P.; Ciesielski, Maciej; Sarabi, Andisheh

doi:10.1109/iscas.1989.100459

Cited by 14 publications

(9 citation statements)

References 7 publications

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“…The DIADES design automation system [14] methodology is oriented towards detecting the linear (EXOR) part of a Boolean function. It uses, among other methods, spectral ones to detect the EXOR part of a Boolean function.…”

Section: Kronecker and Pseudo Kronecker Product Of Twomentioning

confidence: 99%

“…Two design automation systems have used spectral meiliods as the tool for designing of digital circuits [14], [16], [48], [49], and [52]. Computation of the spectrum is a complex operation that requires, in the general case, n 2 n operations of additions/subtractions when the Fast Walsh Transform [24] is used and the Boolean function has n input variables.…”

Section: Kronecker and Pseudo Kronecker Product Of Twomentioning

confidence: 99%

“…The SPECSYS (for SPECtral SYnthesis System) developed at Drexel University on a VAX l1n80 uses the Fast Walsh Transform [24] for the calculation of the spectrum and can process Boolean functions having only 20 input variables [16] and [48]. The DIADES design automation system developed at Portland State University [14] does not have any limit on the number of input variables of Boolean functions that can be processed and uses the methods described in this Dissertation for the generation of spectral coefficients of Boolean functions.…”

Section: Kronecker and Pseudo Kronecker Product Of Twomentioning

confidence: 99%

“…The first method, that allows calculation of the spectrum directly from a Kamaugh map, is introduced here for better understanding of the meaning of spectral coefficients in classical logic terms. The second method has been implemented in the DIADES automation system [14].…”

Section: Kronecker and Pseudo Kronecker Product Of Twomentioning

confidence: 99%

“…Since a direct linear relationship exists between the R and S spectra described by equations (rnA) and (ill.5) then this Chapter uses mainly the S spectrum. The computer method has been implemented in the DIADES automation system [14], [89], [90] and [92].…”

Section: Example Iv5mentioning

confidence: 99%

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Spectral Methods for Boolean and Multiple-Valued Input Logic Functions

Falkowski¹

2000

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Spectral techniques in digital logic design have been known for more than thirty years. They have been used for Boolean function classification, disjoint decomposition, parallel and serial linear decomposition, spectral translation synthesis (extraction of 2 linear pre-and post-filters), multiplexer synthesis, prime implicant extraction by spectral summation, threshold logic synthesis, estimation of logic complexity, testing, and state assignment.This dissertation resolves many important issues concerning the efficient application of spectral methods used in the computer-aided design of digital circuits. The main obstacles in these applications were, up to now, memory requirements for computer systems and lack of the possibility of calculating spectra direcdy from Boolean equations.By using the algorithms presented here these obstacles have been overcome. Moreover, the methods presented in this dissertation can be regarded as representatives of a whole family of methods and the approach presented can 1Y: easily adapted to other orthogonal transforms used in digital logic design. Algorithms are shown for Adding, Arithmetic, and Reed-Muller transforms. However, the main focus of this dissertation is on the efficient computer calculation of Rademacher-Walsh spectra of Boolean functions, since this particular ordering of Walsh transforms is most frequendy used in digital logic design.A theory has been developed to calculate the Rademacher-Walsh transform from a cube array specification of incompletely specified Boolean functions. The importance of representing Boolean functions as arrays of disjoint ON-and DC-cubes has been pointed out, and an efficient new algorithm to generate disjoint cubes from non-disjoint ones has been designed. The transform algorithm makes use of the properties of an array of disjoint cubes and allows the determination of the spectral coefficients in an independent way. By such an approach each spectral coefficient can be calculated separately or all the coefficients can be calculated in parallel. These advantages are absent in the existing methods. The possibility of calculating only some coefficients is very important since there are many spectral methods in digital logic design for which the values of only a few selected coefficients are needed.Most of the current methods used in the spectral domain deal only with completely specified Boolean functions. On the other hand, all of the algorithms introduced here are valid, not only for completely specified Boolean functions, but for functions with don't cares. Don't care minterms are simply represented in the form of disjoint cubes.The links between spectral and classical methods used for designing digital cir- A new algorithm is shown that converts the disjoint cube representation of Boolean functions into fixed-polarity Generalized Reed-Muller Expansions (GRME).Since the known fast algorithm that generates the GR..\1E, based on the factorization of 4 the Reed-Muller transform matrix, always starts from the truth table (mintenns) of a Boole...

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Section: Kronecker and Pseudo Kronecker Product Of Twomentioning

confidence: 99%

Section: Kronecker and Pseudo Kronecker Product Of Twomentioning

confidence: 99%

Section: Kronecker and Pseudo Kronecker Product Of Twomentioning

confidence: 99%

Section: Kronecker and Pseudo Kronecker Product Of Twomentioning

confidence: 99%

Section: Example Iv5mentioning

confidence: 99%

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Spectral Methods for Boolean and Multiple-Valued Input Logic Functions

Falkowski¹

2000

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One more way to calculate generalized Reed-Muller expansions of boolean functions

Falkowski

Perkowski

1991

International Journal of Electronics

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Effective computer methods for the calculation of Rademacher-Walsh spectrum for completely and incompletely specified Boolean functions

Falkowski

Schäfer

Perkowski

1992

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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A theory has been developed to calculate the Rademacher-Walsh transform from a cube a r r a y specification of incompletely specified Boolean functions. T h e importance of representing Boolean functions a s a r r a y s of disjoint ON-a n d Ix-cubes has been pointed out, a n d a n efficient new algorithm to generate disjoint cubes f r o m nondisjoint ones has been designed. The t r a n s f o r m algorithm makes use of the properties of a n a r r a y of disjoint cubes a n d allows the determination of the spectral coefficients in a n independent way. The programs for both algorithms use advantages of C language to speed u p the execution. The comparison of different versions of the algorithm has been carried out. T h e presented algorithm a n d its implementation is the fastest a n d most comprehensive program (having many options) known t o us for the calculation of R ademacher-Walsh transform. It successfully overcomes all drawbacks in the calculation of the t r a n s f o r m f r o m the design automation system based on spectral methods-the SPECSYS system from Drexel University that uses Fast Walsh T r a n sform.

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Integration of logic synthesis and high-level synthesis into the DIADES design automation system

Cited by 14 publications

References 7 publications

Spectral Methods for Boolean and Multiple-Valued Input Logic Functions

Spectral Methods for Boolean and Multiple-Valued Input Logic Functions

One more way to calculate generalized Reed-Muller expansions of boolean functions

Effective computer methods for the calculation of Rademacher-Walsh spectrum for completely and incompletely specified Boolean functions

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