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Automatic Translation of FORTRAN Programs to Vector Form
 ACM Transactions on Programming Languages and Systems
, 1987
"... This paper discusses the theoretical concepts underlying a project at Rice University to develop an automatic translator, called PFC (for Parallel FORTRAN Converter), from FORTRAN to FORTRAN 8x. The Rice project, based initially upon the research of Kuck and others at the University of Illinois [6, ..."
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Cited by 293 (32 self)
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This paper discusses the theoretical concepts underlying a project at Rice University to develop an automatic translator, called PFC (for Parallel FORTRAN Converter), from FORTRAN to FORTRAN 8x. The Rice project, based initially upon the research of Kuck and others at the University of Illinois [6, 1721, 24, 32, 36], is a continuation of work begun while on leave at IBM Research in Yorktown Heights, N.Y. Our first implementation was based on the Illinois PARAFRASE compiler [20, 36], but the current version is a completely new program (although it performs many of the same transformations as PARAFRASE). Other projects that have influenced our work are the Texas Instruments ASC compiler [9, 33], the Cray1 FORTRAN compiler [15], and the Massachusetts Computer Associates Vectorizer [22, 25]. The paper is organized into seven sections. Section 2 introduces FORTRAN 8x and gives examples of its use. Section 3 presents an overview of the translation process along with an extended translation example. Section 4 develops the concept of interstatement dependence and shows how it can be applied to the problem of vectorization. Loop carried dependence and loop independent dependence are introduced in this section to extend dependence to multiple statements and multiple loops. Section 5 develops dependencebased algorithms for code generation and transformations for enhancing the parallelism of a statement. Section 6 describes a method for extending the power of data dependence to control statements by the process of IF conversion. Finally, Section 7 details the current state of PFC and our plans for its continued development
Channel assignment with separation for interference avoidance in wireless networks
 IEEE Transactions on Parallel and Distributed Systems
, 2003
"... Abstract—Given an integer>1, a vector ð 1; 2;...; 1Þ of nonnegative integers, and an undirected graph G ðV;EÞ, an Lð 1; 2;...; 1Þcoloring of G is a function f from the vertex set V to a set of nonnegative integers such that jfðuÞ fðvÞj i, if dðu; vÞ i; 1 i 1, where dðu; vÞ is the distance (i.e., th ..."
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Cited by 22 (5 self)
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Abstract—Given an integer>1, a vector ð 1; 2;...; 1Þ of nonnegative integers, and an undirected graph G ðV;EÞ, an Lð 1; 2;...; 1Þcoloring of G is a function f from the vertex set V to a set of nonnegative integers such that jfðuÞ fðvÞj i, if dðu; vÞ i; 1 i 1, where dðu; vÞ is the distance (i.e., the minimum number of edges) between the vertices u and v. An optimal Lð 1; 2;...; 1Þcoloring for G is one using the smallest range of integers over all such colorings. This problem has relevant application in channel assignment for interference avoidance in wireless networks, where channels (i.e., colors) assigned to interfering stations (i.e., vertices) at distance i must be at least i apart, while the same channel can be reused in vertices whose distance is at least. In particular, two versions of the coloring problem—Lð2; 1; 1Þ and Lð 1; 1;...; 1Þ—are considered. Since these versions of the problem are NPhard for general graphs, efficient algorithms for finding optimal colorings are provided for specific graphs modeling realistic wireless networks, including rings, bidimensional grids, and cellular grids.
On the Impact of Forgetting on Learning Machines
 Journal of the ACM
, 1993
"... this paper contributes toward the goal of understanding how a computer can be programmed to learn by isolating features of incremental learning algorithms that theoretically enhance their learning potential. In particular, we examine the effects of imposing a limit on the amount of information that ..."
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Cited by 10 (3 self)
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this paper contributes toward the goal of understanding how a computer can be programmed to learn by isolating features of incremental learning algorithms that theoretically enhance their learning potential. In particular, we examine the effects of imposing a limit on the amount of information that learning algorithm can hold in its memory as it attempts to This work was facilitated by an international agreement under NSF Grant 9119540.
A FunctionComposition Approach to Synthesize Fortran 90 Array Operations
 Journal of Parallel and Distributed Computing
, 1998
"... An increasing number of programming languages, such as Fortran 90 and APL, are providing a rich set of intrinsic array functions and array expressions. These constructs which constitute an important part of data parallel languages provide excellent opportunities for compiler optimizations. In this p ..."
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Cited by 4 (3 self)
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An increasing number of programming languages, such as Fortran 90 and APL, are providing a rich set of intrinsic array functions and array expressions. These constructs which constitute an important part of data parallel languages provide excellent opportunities for compiler optimizations. In this paper, we present a new approach to combine consecutive array operations or array expressions into a composite access function of the source arrays. Our scheme is based on the composition of access functions, which is analogous to a composition of mathematic functions. Our new scheme can handle not only data movements of arrays with different numbers of dimensions and with multipleclause array operations but also masked array expressions and multiplesource array operations. As a result, our proposed scheme is the first synthesis scheme which can collectively synthesize Fortran 90 RESHAPE, EOSHIFT, MERGE, array reduction operations, and WHERE constructs. In addition, we also discuss the case...
Asynchronous training in wireless sensor networks
 Proc. 3rd AlgoSensors, Wroclaw
, 2007
"... Scalable energyefficient training protocols are proposed for massivelydeployed sensor networks, where sensors are initially anonymous and unaware of their location. The protocols are based on an intuitive coordinate system imposed onto the deployment area which partitions the anonymous sensors int ..."
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Cited by 4 (3 self)
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Scalable energyefficient training protocols are proposed for massivelydeployed sensor networks, where sensors are initially anonymous and unaware of their location. The protocols are based on an intuitive coordinate system imposed onto the deployment area which partitions the anonymous sensors into clusters. The protocols are asynchronous, in the sense that the sensors wake up for the first time at random, then alternate between sleep and awake periods both of fixed length, and no explicit synchronization is performed between them and the sink. Theoretical properties are stated under which the training of all the sensors is possible. Moreover, a worstcase analysis as well as an experimental evaluation of the performance is presented, showing that the protocols are lightweight and flexible. 1
Efficient Binary Schemes for Training Heterogeneous Sensor and Actor Networks
"... Sensor networks are expected to evolve into longlived, autonomous networked systems whose main mission is to provide insitu users – called actors – with realtime information in support of specific goals supportive of their mission. The network is populated with a heterogeneous set of tiny sensors ..."
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Sensor networks are expected to evolve into longlived, autonomous networked systems whose main mission is to provide insitu users – called actors – with realtime information in support of specific goals supportive of their mission. The network is populated with a heterogeneous set of tiny sensors. The free sensors alternate between sleep and awake periods, under program control in response to computational and communication needs. The periodic sensors alternate between sleep periods and awake periods of predefined lengths, established at the fabrication time. The architectural model of an actorcentric network used in this work comprises in addition to the tiny sensors a set of mobile actors that organize and manage the sensors in their vicinity. We take the view that the sensors deployed
1 Efficient Binary Corona Training Protocols for Heterogeneous Sensor and Actor Networks
"... Abstract—Sensor networks are expected to evolve into longlived, autonomous networked systems whose main mission is to provide insitu users – called actors – with realtime information for specific goals supportive of their mission. The network is populated with a heterogeneous set of tiny sensors. ..."
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Abstract—Sensor networks are expected to evolve into longlived, autonomous networked systems whose main mission is to provide insitu users – called actors – with realtime information for specific goals supportive of their mission. The network is populated with a heterogeneous set of tiny sensors. The free sensors alternate between sleep and awake periods, under program control in response to computational and communication needs. The periodic sensors alternate between sleep periods and awake periods of predefined lengths, established at the fabrication time. The architectural model of an actorcentric network used in this work comprises in addition to the tiny sensors a set of mobile actors that organize and manage the sensors in their vicinity. We take the view that the sensors deployed are anonymous and unaware of their geographic location. Importantly, the sensors are not, a priori, organized into a network. It is, indeed, the interaction between the actors and the sensor population that organizes the sensors in a disk around each actor into a shortlived, missionspecific, network that exists for the purpose of serving the actor and that will be disbanded when the interaction terminates. The task of setting up this form of actorcentric network involves a training stage where the sensors acquire dynamic coordinates relative to the actor in their vicinity. The main contribution of this work is to propose an energyefficient training protocol for actorcentric heterogeneous sensor networks. Our protocol outperforms all known training protocols in the number of sleep/awake transitions per sensor needed by the training task. Specifically, in the presence of k coronas, no sensor will experience more than 1+⌈log k ⌉ sleep/awake transitions and awake periods. Index Terms—Autonomous wireless sensor networks, heterogeneous sensor and actor networks, free sensors, periodic sensors, training protocols I.
On the Baseb Expansion of the Number of Trailing Zeros of b k!
"... Let Zb(n) denote the number of trailing zeroes in the baseb expansion of n!. In this paper we study the connection between the expression of ϑ(b): = limn→ ∞ Zb(n)/n in base b, and that of Zb(b k). In particular, if b is a prime power, we will show the equality between the k digits of Zb(b k) and th ..."
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Let Zb(n) denote the number of trailing zeroes in the baseb expansion of n!. In this paper we study the connection between the expression of ϑ(b): = limn→ ∞ Zb(n)/n in base b, and that of Zb(b k). In particular, if b is a prime power, we will show the equality between the k digits of Zb(b k) and the first k digits in the fractional part of ϑ(b). In the general case we will see that this equality still holds except for, at most, the last ⌊log b(k) + 3 ⌋ digits. We finally show that this bound can be improved if b is squarefree and present some conjectures about this bound. 1
1 Efficient Location Training Protocols for Heterogeneous Sensor and Actor Networks
"... Abstract—In this work we consider a largescale geographic area populated by tiny sensors and some more powerful devices called actors, authorized to organize the sensors in their vicinity into shortlived, actorcentric sensor networks. The tiny sensors run on miniature nonrechargeable batteries, ..."
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Abstract—In this work we consider a largescale geographic area populated by tiny sensors and some more powerful devices called actors, authorized to organize the sensors in their vicinity into shortlived, actorcentric sensor networks. The tiny sensors run on miniature nonrechargeable batteries, are anonymous and are unaware of their location. The sensors differ in their ability to dynamically alter their sleep times. Indeed, the periodic sensors have sleep periods of predefined lengths, established at fabrication time; by contrast, the free sensors can dynamically alter their sleep periods, under program control. The main contribution of this work is to propose an energyefficient location training protocol for heterogeneous actorcentric sensor networks where the sensors acquire coarsegrain location awareness with respect to the actor in their vicinity. Our analytical analysis, confirmed by experimental evaluation, show that the proposed protocol outperforms the best previouslyknown location training protocols in terms of the number of sleep/awake transitions, overall sensor awake time, and energy consumption. Index Terms—Sensor and actor networks, heterogeneous sensors, coarsegrain localization, location training protocols, localization protocols I.
ON CONSECUTIVE NIVEN NUMBERS
, 1991
"... In [1] the concept of a Niven number was introduced with the following definition. Definition: A positive integer is called a Niven number if it is divisible by its digital sum. Various articles have appeared concerning digital sums and properties of the set of Niven numbers. In particular, it was s ..."
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In [1] the concept of a Niven number was introduced with the following definition. Definition: A positive integer is called a Niven number if it is divisible by its digital sum. Various articles have appeared concerning digital sums and properties of the set of Niven numbers. In particular, it was shown in [2] that no more than 21 consecutive Niven numbers is