Computer Architecture

This paper first theoretically analyzes the influence of loop-carried dependence on software pipelining. It then defines two loop categories: restrictable and unrestrictable loops, puts forward and proves a sufficient and necessary condition for distinguishing the two kinds of loops. This condition is related with the number of operation pairs with loop-carried dependence, the execution time of operations, and other loop parameters. Next, this paper proves that any unrestrictable loop can be transformed into a semantically equivalent restrictable loop by unrolling K times. K is determined by the number of operation pairs with loop-carried dependence within the original unrestrictable loop. Finally, the paper presents a general URPR software pipelining approach which consists of a pre-processing algorithm, a new compaction algorithm for a loop body and a URPR algorithm. Preliminary experiments show that the general URPR can guarantee a time-optimal result for any loop in the absence ...

... Bogong Suf, Wei Zhao$, and Zhizhong Tang ... Thisswkhuboc.ptidlymp,tdbyNatimdSmrrF~tianofCbkm ~CIln.riAddrru:Dcpc.dCanpuLorScima,ThcColkpcofSLstcnlrlPrd Tk City U&m&y d New Yak, 130 SW plsa, Staten Mad, NY 103Ql Emnil:BSUSI@CUNYVM.CUNY.FDU Tel:718 ...

... Bogong Su, Jian Wang,Fhi~hgr~g Wei Zhao an Tang, a rimm wu Dept. ... Second, try to guarantee that Vi& (1.2vM) 1 use(PEi, FU) - use(PEj, FU) 1 FUE (fonction tmir set) is minimal, where use(PEk, FU) is the number of use of FU by the PEk segment in the new loop body. ...

ABSTRACT This paper first theoretically analyzes the influence of loop-carried dependence on software pipelining. It then defines two loop categories: restrictable and unrestrictable loops, puts forward and proves a sufficient and necessary condition for distinguishing the two kinds of loops. This condition is related with the number of operation pairs with loop-carried dependence, the execution time of operations, and other loop parameters. Next, this paper proves that any unrestrictable loop can be transformed into a semantically equivalent restrictable loop by unrolling K times. K is determined by the number of operation pairs with loop-carried dependence within the original unrestrictable loop. Finally, the paper presents a general URPR software pipelining approach which consists of a pre-processing algorithm, a new compaction algorithm for a loop body and a URPR algorithm. Preliminary experiments show that the general URPR can guarantee a time-optimal result for any loop in the absence of resource constraints and still keep good space efficiency and low complexity

Researchers have argued that an attentional mechanism is required to perform many vision tasks. In this paper we propose an approach to object classification that is based on the multi layer perceptron neural network implemented on the selective tuning model, in order to classify the scan-path of an object. A form of scan-path is obtained using the selective tuning model. The neural network takes as input this scan-path and gives, as output, the estimated class. The entire structure can learn, from a wide variety of examples, how to classify scan-path patterns in a supervised manner and then to recognize objects in digital images. This model of selective visual attention provides for a solution to the problems of selection in an image and information routing through the visual processing hierarchy. This approach is described in some detail and a performance example of scan-path classification is shown. The results confirm that the selective tuning model is both robust and fast.

Autonomous underwater vehicles (AUVs) have many, scientific, military, and commercial applications because of their potential capabilities and significant cost-performance improvements. Typical AUV development requires critical system design and many costly at-sea trials during which systems specifications can be validated. Modeling and simulation provides a cost-effective method for carrying out preliminary component or system (hardware and software) testing and verification. Due

Abstract The link delivery probability in a wireless mesh network is most accurately determined only by experiment, as it depends on many factors, including environment characteristics, transmission power, distance between transmitter and receiver, channel fading, and background noise. This paper provides an insightful framework for characterizing link performance results produced at Qatar University (QU) wireless mesh test-bed under harsh environmental conditions, including heavy buildings structure, mixed ...