1,036 research outputs found
Pruned Bit-Reversal Permutations: Mathematical Characterization, Fast Algorithms and Architectures
A mathematical characterization of serially-pruned permutations (SPPs)
employed in variable-length permuters and their associated fast pruning
algorithms and architectures are proposed. Permuters are used in many signal
processing systems for shuffling data and in communication systems as an
adjunct to coding for error correction. Typically only a small set of discrete
permuter lengths are supported. Serial pruning is a simple technique to alter
the length of a permutation to support a wider range of lengths, but results in
a serial processing bottleneck. In this paper, parallelizing SPPs is formulated
in terms of recursively computing sums involving integer floor and related
functions using integer operations, in a fashion analogous to evaluating
Dedekind sums. A mathematical treatment for bit-reversal permutations (BRPs) is
presented, and closed-form expressions for BRP statistics are derived. It is
shown that BRP sequences have weak correlation properties. A new statistic
called permutation inliers that characterizes the pruning gap of pruned
interleavers is proposed. Using this statistic, a recursive algorithm that
computes the minimum inliers count of a pruned BR interleaver (PBRI) in
logarithmic time complexity is presented. This algorithm enables parallelizing
a serial PBRI algorithm by any desired parallelism factor by computing the
pruning gap in lookahead rather than a serial fashion, resulting in significant
reduction in interleaving latency and memory overhead. Extensions to 2-D block
and stream interleavers, as well as applications to pruned fast Fourier
transforms and LTE turbo interleavers, are also presented. Moreover,
hardware-efficient architectures for the proposed algorithms are developed.
Simulation results demonstrate 3 to 4 orders of magnitude improvement in
interleaving time compared to existing approaches.Comment: 31 page
Parallel computation of entries of A-1
In this paper, we are concerned about computing in parallel several entries of the inverse of a large sparse matrix. We assume that the matrix has already been factorized by a direct method and that the factors are distributed. Entries are efficiently computed by exploiting sparsity of the right-hand sides and the solution vectors in the triangular solution phase. We demonstrate that in this setting, parallelism and computational efficiency are two contrasting objectives. We develop an efficient approach and show its efficacy by runs using the MUMPS code that implements a parallel multifrontal method
On chip interconnects for multiprocessor turbo decoding architectures
International audienc
Asymptotic Analysis of Plausible Tree Hash Modes for SHA-3
Discussions about the choice of a tree hash mode of operation for a
standardization have recently been undertaken. It appears that a single tree
mode cannot address adequately all possible uses and specifications of a
system. In this paper, we review the tree modes which have been proposed, we
discuss their problems and propose remedies. We make the reasonable assumption
that communicating systems have different specifications and that software
applications are of different types (securing stored content or live-streamed
content). Finally, we propose new modes of operation that address the resource
usage problem for the three most representative categories of devices and we
analyse their asymptotic behavior
Hybrid language processing in the Spoken Language Translator
The paper presents an overview of the Spoken Language Translator (SLT)
system's hybrid language-processing architecture, focussing on the way in which
rule-based and statistical methods are combined to achieve robust and efficient
performance within a linguistically motivated framework. In general, we argue
that rules are desirable in order to encode domain-independent linguistic
constraints and achieve high-quality grammatical output, while corpus-derived
statistics are needed if systems are to be efficient and robust; further, that
hybrid architectures are superior from the point of view of portability to
architectures which only make use of one type of information. We address the
topics of ``multi-engine'' strategies for robust translation; robust bottom-up
parsing using pruning and grammar specialization; rational development of
linguistic rule-sets using balanced domain corpora; and efficient supervised
training by interactive disambiguation. All work described is fully implemented
in the current version of the SLT-2 system.Comment: 4 pages, uses icassp97.sty; to appear in ICASSP-97; see
http://www.cam.sri.com for related materia
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