Systolic convolution of arithmetic functions

AbstractGiven two arithmetic functions f and g, their convolution h=f∗g is defined as h(n)=Σkl=n,1⩽k,l⩽nf(k)g(l) for all n⪖1. Given two arithmetic functions g and h, the inverse convolution problem is to determine f such that f∗g=h.In this paper, we propose two linear arrays for the real-time computation of the convolution and the inverse convolution problem. These arrays extend the design of Verhoeff for the computation of the Möbius function μ, defined as the solution of the inverse convolution problem μ∗g=Δ, where g(n)=1 for all n⩾1 and Δ(n)=1 if n=1, Δ(n)=0 if n>1

Systolic convolution of arithmetic functions

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A new matrix multiplication systolic array

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Disruption-Tolerant Wireless Biomedical Monitoring for Marathon Runners: a Feasibility Study

International audienceOff-the-shelf wireless sensing devices open a wide range of perspectives for tetherless biomedical monitoring. Yet most applications considered to date imply either indoor realtime data streaming or ambulatory data recording. Disruption-tolerant networking is a means to cope with challenging situations where continuous end-to-end connectivity between communicating devices cannot be guaranteed. In this paper we investigate the possibility of using this approach to remotely monitor the cardiac activity of runners during a marathon race, using off-the shelf sensing devices and a limited number of base stations deployed along the marathon route. Preliminary experiments show that such a scenario is indeed viable, although special attention must be paid to balancing the requirements of ECG monitoring with the constraints of episodic, low-rate transmissions

Biomedical Monitoring of Non-Hospitalized Subjects using Disruption-Tolerant Wireless Sensors

International audienceThe proliferation of private, corporate and community Wi-Fi hotspots in city centers and residential areas opens up new opportunities for the collection of biomedical data produced by sensors carried by mobile non-hospitalized subjects. In this paper we investigate the possibility of using these many hotspots as gateways for biomedical data transmission. A disruption-tolerant application is presented, that can record biomedical data while the subject is not in the range of a Wi-Fi hotspot, and upload recorded data to a remote monitoring center whenever a hotspot is located nearby. Results of a field trial are presented, with a scenario involving a subject wearing an ECG-enabled sensor, walking in the streets of a residential area

A new matrix multiplication systolic array

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Accelerating HMMER on FPGA using Parallel Prefixes and Reductions

HMMER is a widely used tool in bioinformatics, based on Profile Hidden Markov Models. The computation kernels of HMMER i.e. MSV and P7Viterbi are very compute intensive and data dependencies restrict to sequential execution. In this paper, we propose an original parallelization scheme for HMMER by rewriting their mathematical formulation, to expose the hidden potential parallelization opportunities. Our parallelization scheme targets FPGA technology, and our architecture can achieve 10 times speedup compared with that of latest HMMER3 SSE version, while not compromising on sensitivity of original algorithm.HMMER est un outil basé sur la notion profils à base modèles de Markov cachés, qui est très largement utilisé en bio-informatique. Les parties critiques de l'algorithme (fonctions MSV et P7Viterbi) utilisées dans HMMER sont très consommatrices en temps de calcul et réputées très difficiles à paralléliser. Dans cet article, nous proposons un schéma de parallélisation original pour HMMER, basé sur une reformulation mathématique de l'algorithme qui permet de découvrir de nouvelles possibilités de parallélisation bien adaptées à des implantations matérielles dédiées. Nous avons implanté cette approche sur un accélérateur FPGA et avons mesuré des gains en performance supérieurs à 10 par rapport à l'implémentation logicielle de HMMER3, laquelle exploite pourtant déjà de manière extrêmement efficace les extensions SIMD des processeurs x8

Alpha Du Centaur : a prototype environment for the design of parallel regular algorithms

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The Naive Execution of Affine Recurrence Equations

: In recognition of the fundamental relation between regular arrays and systems of affine recurrence equations, the Alpha language was developed as the basis of a computer aided design methodology for regular array architectures. Alpha is used to initially specify algorithms at a very high algorithmic level. Regular array architecures can then be derived from the algorithmic specification using a transformational approach supported by the Alpha environment. This design methodology guarantees the final design to be correct by construction, assuming the initial algorithm was correct. In this paper, we address the problem of validating an initial specification. We demonstrate a translation methodolody which compiles Alpha into the imperative sequential language C. The C--code may then be compiled and executed to test the specification. We show how an Alpha program can be naively implemented by viewing it as a set of monolithic arrays and their filling functions, implemented using applicat..