A common distributed language approach to software integration

An important objective in software integration is the development of techniques to allow programs written in different languages to function together. Several approaches are discussed toward achieving this objective and the Common Distributed Language Approach is presented as the approach of choice

Hierarchical gate-array routing on a hypercube multiprocessor

Gate-arrays are the most common design style for semicustom VLSI integrated circuits. An important part of the gate-array design process is the routing of wires between the logic elements, which is an extremely compute-intensive operation. This paper presents an algorithm for routing gate-arrays that uses a hypercube connected parallel processor to provide the necessary computation power. In order to make optimal use of the hypercube, the routing algorithm is organized so that interprocessor communication is kept to minimum. It occurs only during the global routing and crossing placement phases of the algorithm, which constitute less than 15% of the total running time of the algorithm. On the basis of the results of executing the algorithm on two gate-array benchmarks the case is made for using hypercube multiprocessors as accelerators for compute-intensive CAD operations.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28650/1/0000466.pd

Automatic Performance Setting for Dynamic Voltage Scaling

The emphasis on processors that are both low power and high performance has resulted in the incorporation of dynamic voltage scaling into processor designs. This feature allows one to make fine granularity tradeoffs between power use and performance, provided there is a mechanism in the OS to control that tradeoff. In this paper, we describe a novel software approach to automatically controlling dynamic voltage scaling in order to optimize energy use. Our mechanism is implemented in the Linux kernel and requires no modification of user programs. Unlike previous automated approaches, our method works equally well with irregular and multiprogrammed workloads. Moreover, it has the ability to ensure that the quality of interactive performance is within user specified parameters. Our experiments show that as a result of our algorithm, processor energy savings of as much as 75% can be achieved with only a minimal impact on the user experience.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41391/1/11276_2004_Article_5091297.pd

Vision algorithms for hypercube machines

Several commercial hypercube parallel processors with the potential to deliver massive parallelism cost-effectively have been announced recently. They open the door to a wide variety of application areas that could benefit from parallelism. Computer vision is one of these application areas. This paper develops a general model for hypercube machines, and uses it to show how vision algorithms can be executed on hypercubes. In particular, the steps in the problem of thick-film inspection are used as a concrete example. The time needed to complete a typical inspection is used to demonstrate the performance of hypercube machines. Experimental results from a hypercube machine illustrate the potential use of such machines.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26820/1/0000379.pd

Hierarchical decomposition and simulation of manufacturing cells using Ada

A useful tool in the development of flexible automation is a system description language which can generate a complete func tional description of a manufacturing cell of arbitrary complexity. We propose a description system based on the concept of hierar chical decomposition utilizing the Ada programming language in conjunction with established diagrammatical decomposition methods. The distinguishing aspect of our work is that it takes advantage of certain features of Ada (such as type checking) to create a description that can be automatically verified for con sistency Simulation is often an indispensable tool in the develop ment of manufacturing systems. We show how a simulation of the operation of the manufacturing cell can be embedded in its description. Finally, we apply the methodology to a specific instance of a manufacturing cell.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68498/2/10.1177_003754978604600402.pd

LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft

EXA2PRO programming environment:Architecture and applications

The EXA2PRO programming environment will integrate a set of tools and methodologies that will allow to systematically address many exascale computing challenges, including performance, performance portability, programmability, abstraction and reusability, fault tolerance and technical debt. The EXA2PRO tool-chain will enable the efficient deployment of applications in exascale computing systems, by integrating high-level software abstractions that offer performance portability and efficient exploitation of exascale systems' heterogeneity, tools for efficient memory management, optimizations based on trade-offs between various metrics and fault-tolerance support. Hence, by addressing various aspects of productivity challenges, EXA2PRO is expected to have significant impact in the transition to exascale computing, as well as impact from the perspective of applications. The evaluation will be based on 4 applications from 4 different domains that will be deployed in JUELICH supercomputing center. The EXA2PRO will generate exploitable results in the form of a tool-chain that support diverse exascale heterogeneous supercomputing centers and concrete improvements in various exascale computing challenges

Efficient Recognition of Partially Visible Objects Using a Logarithmic Complexity Matching Technique

An important task in computer vision is the recognition of partially visible two-dimensional objects in a gray scale image. Recent works addressing this problem have attempted to match spatially local features from the image to features generated by models of the objects. However, many algo rithms are considerably less efficient than they might be, typ ically being O(IN) or worse, where I is the number offeatures in the image and N is the number of features in the model set. This is invariably due to the feature-matching portion of the algorithm. In this paper we discuss an algorithm that significantly improves the efficiency offeature matching. In addition, we show experimentally that our recognition algo rithm is accurate and robust. Our algorithm uses the local shape of contour segments near critical points, represented in slope angle-arclength space (θ-s space), as fundamental fea ture vectors. These feature vectors are further processed by projecting them onto a subspace in θ-s space that is obtained by applying the Karhunen-Loève expansion to all such fea tures in the set of models, yielding the final feature vectors. This allows the data needed to store the features to be re duced, while retaining nearly all information important for recognition. The heart of the algorithm is a technique for performing matching between the observed image features and the precomputed model features, which reduces the runtime complexity from O(IN) to O(I log I + I log N), where I and N are as above. The matching is performed using a tree data structure, called a kD tree, which enables multidi mensional searches to be performed in O(log) time.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66975/2/10.1177_027836498900800608.pd

Cache coherence requirements for interprocess rendezvous

Multiprocessors in which a shared bus is used by the processor to communicate with common memory are an emerging class of machines where there is a need to support parallel programming languages. A language construct that is found in a number of parallel programming languages to support synchronization and communication in the interprocess rendezvous. Shared-bus multiprocessor require a protocol to keep the date in their caches coherent. There are two major categories of these protocols: invalidation and write-boadcast. This paper examines the requirements for cache coherence protocols to support efficient interprocessor rendezvous. The approach taken is to examine the memory referencing patterns to the run-time data structures during rendezvous execution. The appropriate coherence protocol is shown to be a function of the processor scheduling strategy used by the run-time system at synchronzation points during the rendezvous. When processes migrate freely as a result of the scheduling strategy, invalidation protocols are found to be more efficient. When migration is restricted by the scheduler, write-broadcast protocols are more efficient.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44571/1/10766_2005_Article_BF01407863.pd

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder