87,165 research outputs found
Formal Verification of an Iterative Low-Power x86 Floating-Point Multiplier with Redundant Feedback
We present the formal verification of a low-power x86 floating-point
multiplier. The multiplier operates iteratively and feeds back intermediate
results in redundant representation. It supports x87 and SSE instructions in
various precisions and can block the issuing of new instructions. The design
has been optimized for low-power operation and has not been constrained by the
formal verification effort. Additional improvements for the implementation were
identified through formal verification. The formal verification of the design
also incorporates the implementation of clock-gating and control logic. The
core of the verification effort was based on ACL2 theorem proving.
Additionally, model checking has been used to verify some properties of the
floating-point scheduler that are relevant for the correct operation of the
unit.Comment: In Proceedings ACL2 2011, arXiv:1110.447
Computing hypergeometric functions rigorously
We present an efficient implementation of hypergeometric functions in
arbitrary-precision interval arithmetic. The functions , ,
and (or the Kummer -function) are supported for
unrestricted complex parameters and argument, and by extension, we cover
exponential and trigonometric integrals, error functions, Fresnel integrals,
incomplete gamma and beta functions, Bessel functions, Airy functions, Legendre
functions, Jacobi polynomials, complete elliptic integrals, and other special
functions. The output can be used directly for interval computations or to
generate provably correct floating-point approximations in any format.
Performance is competitive with earlier arbitrary-precision software, and
sometimes orders of magnitude faster. We also partially cover the generalized
hypergeometric function and computation of high-order parameter
derivatives.Comment: v2: corrected example in section 3.1; corrected timing data for case
E-G in section 8.5 (table 6, figure 2); adjusted paper siz
DSPSR: Digital Signal Processing Software for Pulsar Astronomy
DSPSR is a high-performance, open-source, object-oriented, digital signal
processing software library and application suite for use in radio pulsar
astronomy. Written primarily in C++, the library implements an extensive range
of modular algorithms that can optionally exploit both multiple-core processors
and general-purpose graphics processing units. After over a decade of research
and development, DSPSR is now stable and in widespread use in the community.
This paper presents a detailed description of its functionality, justification
of major design decisions, analysis of phase-coherent dispersion removal
algorithms, and demonstration of performance on some contemporary
microprocessor architectures.Comment: 15 pages, 10 figures, to be published in PAS
Globally Optimal Cell Tracking using Integer Programming
We propose a novel approach to automatically tracking cell populations in
time-lapse images. To account for cell occlusions and overlaps, we introduce a
robust method that generates an over-complete set of competing detection
hypotheses. We then perform detection and tracking simultaneously on these
hypotheses by solving to optimality an integer program with only one type of
flow variables. This eliminates the need for heuristics to handle missed
detections due to occlusions and complex morphology. We demonstrate the
effectiveness of our approach on a range of challenging sequences consisting of
clumped cells and show that it outperforms state-of-the-art techniques.Comment: Engin T\"uretken and Xinchao Wang contributed equally to this wor
Scaling laws governing stochastic growth and division of single bacterial cells
Uncovering the quantitative laws that govern the growth and division of
single cells remains a major challenge. Using a unique combination of
technologies that yields unprecedented statistical precision, we find that the
sizes of individual Caulobacter crescentus cells increase exponentially in
time. We also establish that they divide upon reaching a critical multiple
(1.8) of their initial sizes, rather than an absolute size. We show
that when the temperature is varied, the growth and division timescales scale
proportionally with each other over the physiological temperature range.
Strikingly, the cell-size and division-time distributions can both be rescaled
by their mean values such that the condition-specific distributions collapse to
universal curves. We account for these observations with a minimal stochastic
model that is based on an autocatalytic cycle. It predicts the scalings, as
well as specific functional forms for the universal curves. Our experimental
and theoretical analysis reveals a simple physical principle governing these
complex biological processes: a single temperature-dependent scale of cellular
time governs the stochastic dynamics of growth and division in balanced growth
conditions.Comment: Text+Supplementar
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