An analysis of the aliasing probability of multiple-input signature registers in the case of a 2/sup m/-ary symmetric channel

Iwasaki, Kei; Arakawa, Fumio

doi:10.1109/43.45874

Cited by 54 publications

(8 citation statements)

References 13 publications

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“…Starting from equation (3) and summing over lengths K = 1, K = 2, we obtained the series (1 -p)r-W-lpW ~ K(1 -p)tr (12) K=I Since p is a probability between 0 and 1, the series in (12) has a closed form and (12) reduces to (1 -p)L-WpW-2 (13) For p = 0 it is safe to ignore the convergence problems of the series in (12) since (3) is 0 for p = 0 and W > 0. Starting from equation (3) and summing over lengths K = 1, K = 2, we obtained the series (1 -p)r-W-lpW ~ K(1 -p)tr (12) K=I Since p is a probability between 0 and 1, the series in (12) has a closed form and (12) reduces to (1 -p)L-WpW-2 (13) For p = 0 it is safe to ignore the convergence problems of the series in (12) since (3) is 0 for p = 0 and W > 0.…”

Section: Vol(ep) ---The Normalized Value Of V(ep) Obtained By Multiplmentioning

confidence: 99%

Aliasing probability transients

Robinson

1992

J Electron Test

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Test data reduction for digital systems is often accomplished through the use of a feedback shift register. This method, known as signature analysis, can exhibit error masking or aliasing. Recent analysis has shown that the use of a primitive polynomial for the register feedback can reduce the probability of aliasing. In this work we demonstrate that not all primitive polynomials are created equal. Some primitive polynomials can have very large transients in their aliasing probability. For example, 1 + X 13 + X 33 can exhibit an aliasing probability more than a million times larger than its asymptotic value of 2-33. An evaluation procedure is presented which can identify polynomials with good transient characteristics. Some recommended feedback polynomials are given.

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Section: Vol(ep) ---The Normalized Value Of V(ep) Obtained By Multiplmentioning

confidence: 99%

Aliasing probability transients

Robinson

1992

J Electron Test

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“…12. Error models: -2 %~ symmetric channel error model [9] for the errors associated with the rn-bit address words in the routing process. We assume that the compression device is a MISR [13], shown in FIG.…”

Section: Line Monitoring Melthodmentioning

confidence: 99%

“…The error-jree signature is: The aliasing probability Pal(n) for an MISR can be derived based on the coding theory and is given in [9] :…”

Section: B) the Error Detection! At The Destination In T H E E R R O mentioning

confidence: 99%

See 1 more Smart Citation

A Concurrent Test Architecture for Massively-Parallel Computers and Its Error Detection Capability

Hancu

Iwasaki

Suzuki

et al.

1991, Proceedings. International Test Conference

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New principles for the on-line system-level test of multiprocessors are proposed, based on signaturing and monitoring data dependences together with control dependences. I n order to help in this process, each data routing message contains both source and destination addresses. At each message source, the destination addresses of the outgoing messages are compressed. At the same time, at each destination, the source addresses of all incoming messages are compressed. Concurrent compression of the instructions executed by the PES is also possible. The resulting signatures are compared at the end of each computational block with reference signatures created at compilation time.An analytical model and an analysis for the address compression process used for the monitoring the data routing process are provided. The aliasing probability for the error detection process is studied, obtaining closedform expressions in the single error case and upper bounds in the multiple error case.INTERNATIONAL TEST CONFERENCE 1 9 9 1 CH3032-0/91/0000-0758$01 .OO@ 1 9 9 1 IEEE In a uniprocessor, the dependences are practically limited to the time domain (defining an order of precedence), while in the multiprocessors, the spatial component is equally important, defining between which processing elements (PES) data transfers take place.In a stricter taxonomy, one can also identify communication dependences in an MPC. They indicate communication paths existing between processor elements (or routers) in an MPC. As for the small-grain PES they practically overlap with the data dependences, we will no1 Paper 28.1

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“…In [22] a closed form expression for exact aliasing probability is derived for multiple input LFSRs with primitive feedback polynomials for any test length. Iwasaki and Arakawa [23] showed that die aliasing probability over a q-ary symmetric channel does not depend on the polynomial that characterizes the multiple input LFSR. In [26] by modeling the signature analyzer as a two-state (all-zero state and non-zero state) Markov process it is shown that the closed form expression derived for aliasing probability in [22], for multiple input LFSRs with primitive polynomials holds for any Multiple-Input LASR (MILASR) (including all multiple-input LFSRs and a class of linear cellular automata) in which the all-zero state cannot be reached from the non-zero state in the absence of an e m .…”

Section: ) Introductionmentioning

confidence: 99%