Benchmarking the CM-5 for Image Processing Applications

This paper presents benchmarking results for image processing algorithms on the Connection Machine model CM-5 and compares them with the results from the CM-2 and the Sun-4. Image processing algorithms with varying communication and computational requirements were implemented, tested and timed. The performance and the scalabilty of the CM-5 were analyzed and compared with that of the CM-2

Hypercube Algorithms for Operations on Quadtrees

This paper describes parallel algorithms for the following operations on quadtrees - boolean operations (union, intersection, complement), collapsing a quadtree, and neighbor finding in an image represented by a quadtree. The architecture assumed in this paper is a hypercube with one processing element (PE) per hypercube node. We assume that the architecture is SIMD, i.e., all PEs work under the control of a single control unit

Origin of charge density wave formation in insulators from a high resolution photoemission study of BaIrO3

We investigate the origin of charge density wave (CDW) formation in insulators by studying BaIrO3 using high resolution (1.4 meV) photoemission spectroscopy. The spectra reveal the existence of localized density of states at the Fermi level in the vicinity of room temperature. These localized states are found to vanish as the temperature is lowered thereby, opening a soft gap at the Fermi level, as a consequence of CDW transition. In addition, the energy dependence of the spectral density of states reveals the importance of magnetic interactions, rather than well-known Coulomb repulsion effect, in determining the electronic structure thereby implying a close relationship between ferromagnetism and CDW observed in this compound. Also, Ba core level spectra surprisingly exhibit an unusual behavior prior to CDW transition.Comment: 4 pages, 4 figures. To appear in Physical Review Letter

Parallel Vision Algorithms Using Sparse Array Representations

Sparse arrays are arrays in which the number of non-zero elements is a small fraction of the total number of array elements. This paper presents computer vision algorithms using sparse representations for arrays. The parallel architecture considered is a hypercube. The algorithms can be easily modified for other architectures like the mesh. We assume that the architecture is SIMD, i.e., all PEs work under the control of a single control unit

The Transportation Primitive

This paper presents algorithms for implementing the transportation primitive on a distributed memory parallel architecture. The transportation primitive performs many-to-many personalized communication with bounded incoming and outgoing traffic. We present a two-stage deterministic algorithm that decomposes the communication with possibly high variance in message size into two communication stages with low message size variance. If the maximum outgoing or incoming traffic at any processor is t, transportation can be done in 2t¯ time (+ lower order terms) when t O(p 2 + pø=¯) (¯ is the inverse of the data transfer rate, ø is the startup overhead). If the maximum outgoing and incoming traffic are r and c respectively, transportation can be done in (r+c)¯ time when either r O(p 2 ) or c O(p 2 ). Optimality and scalability are thus achieved when the traffic is large, a condition that is usually satisfied in practice. The algorithm was implemented on the Connection Machine CM-5. The implementation used the low latency communication primitives (active messages) available on the CM 5, but the algorithm as such is architecture independent. An alternate single-stage algorithm using distributed random scheduling was implemented on the CM-5 and the performance of the two algorithms were compared

Productivity improvement of a computer hardware supply chain.

Abstract Purpose -To determine the key reverse logistics variables, which the top management should focus so as to improve the productivity and performance of computer hardware supply chains. Design/methodology/approach -In this paper, an interpretive structural modeling (ISM) based approach has been employed to model the reverse logistics variables typically found in computer hardware supply chains. These variables have been categorized under "enablers" and "results". The enablers are the variables that help boost the reverse logistics variables, while results variables are the outcome of good reverse logistics practices. Findings -A key finding of this modeling is that environmental concern is the primary cause of the initiation of reverse logistics practices in computer hardware supply chains. For better results, top management should focus on improving the high driving power enabler variables such as regulations, environmental concerns, top management commitment, recapturing value from used products, resource reduction, etc. Originality/value -In this research, an interpretation of reverse logistics variables in terms of their driving and dependence powers has been carried out. Those variables possessing higher driving power in the ISM need to be taken care on a priority basis because there are a few other dependent variables being affected by them. Variables emerging with high dependence contribute to productivity and performance of green supply chain