{"title":"Static program decomposition among machines in an SIMD/SPMD heterogeneous environment with non-constant mode switching costs","authors":"D. Watson, J. Antonio, H. Siegel, M. Atallah","doi":"10.1109/HCW.1994.324961","DOIUrl":"https://doi.org/10.1109/HCW.1994.324961","url":null,"abstract":"The problem of minimizing the execution time of programs within a heterogeneous environment is considered. Different computational characteristics within a parallel algorithm may make switching execution from one machine to another beneficial; however, the cost of switching between machines during the execution of a program must be considered. This cost is not constant, but depends on data transfers needed as a result of the move. Therefore, determining a minimum-cost assignment of machines to program segments is not straightforward. A previously presented block-based mode selection (BBMS) approach is used as a basis to develop a heuristic method for assigning machines to program segments of data-parallel algorithms. Simulation results of parallel program behavior using the heuristic indicate that good assignments are possible without resorting to exhaustive search techniques.<<ETX>>","PeriodicalId":327341,"journal":{"name":"Proceedings Heterogeneous Computing Workshop","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122030445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A framework for the Virtual Heterogeneous Associative Machine","authors":"S. Scott, J. Potter","doi":"10.1109/HCW.1994.324956","DOIUrl":"https://doi.org/10.1109/HCW.1994.324956","url":null,"abstract":"The authors give an overview of the Heterogeneous Associative Computing paradigm (HAsC) for heterogeneous computing, being developed at Kent State University. They then discuss the concept of the Virtual Heterogeneous Associative Machine (VHAM) which is an augmented view of the virtual machine concept as it applies to HAsC. The VHAM instruction set is then outlined along with the meta-commands used to maintain the instructions. Last the VHAM Administrator is introduced and discussed as that portion of HAsC which maintains the VHAM and facilitates the associative principles applied in HAsC.<<ETX>>","PeriodicalId":327341,"journal":{"name":"Proceedings Heterogeneous Computing Workshop","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121006729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Designs and experiments on heterogeneous mapping heuristics","authors":"C. Leangsuksun, J. Potter","doi":"10.1109/HCW.1994.324967","DOIUrl":"https://doi.org/10.1109/HCW.1994.324967","url":null,"abstract":"We have developed and studied various mapping heuristics for a heterogeneous processing (HP) environment. We modify the mapping mechanisms with different communication considerations, processor selection, and mapping refinement policies. We then compare the results from the heuristics with past effort. Experiments indicate that our methods give a significant improvement over previous research.<<ETX>>","PeriodicalId":327341,"journal":{"name":"Proceedings Heterogeneous Computing Workshop","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124020819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Bhattacharya, D. Du, A. Pavan, Sheau-Ru Tong, R. Vetter, K. A. Williams
{"title":"A network architecture for distributed high performance heterogeneous computing","authors":"S. Bhattacharya, D. Du, A. Pavan, Sheau-Ru Tong, R. Vetter, K. A. Williams","doi":"10.1109/HCW.1994.324954","DOIUrl":"https://doi.org/10.1109/HCW.1994.324954","url":null,"abstract":"Network computing has the potential for dramatically increasing the amount of computing power available to large scale compute intensive applications. The authors describe a network architecture upon which a high performance distributed computing environment may be constructed. The architecture uses a specially designed time and wavelength division multiplexed (TWDM) optical passive star as the underlying high speed network. The network architecture is flexible enough to support the many different communication patterns of distributed applications by embedding a computation directly within the system hardware.<<ETX>>","PeriodicalId":327341,"journal":{"name":"Proceedings Heterogeneous Computing Workshop","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132241916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Partitioning of image processing tasks on heterogeneous computer systems","authors":"M. A. Iqbal, S. Iqbal, M. Shaaban","doi":"10.1109/HCW.1994.324963","DOIUrl":"https://doi.org/10.1109/HCW.1994.324963","url":null,"abstract":"Many computer vision tasks can be decomposed into a set of subtasks which are by their nature heterogeneous. By partitioning such tasks onto different machines that communicate via high-speed links, each level or stage of processing can be executed simultaneously on the machine to which it is best suited. A fundamental problem with heterogeneous computing, however, is the difficulty of optimally partitioning an application program across the machines. In this paper, we address the problem of partitioning a chain or a tree-structured parallel or pipelined program over a two-processor heterogeneous system and show that it is possible to approximately solve this problem. The algorithm presented in this paper is based on a fully polynomial time approximation scheme.<<ETX>>","PeriodicalId":327341,"journal":{"name":"Proceedings Heterogeneous Computing Workshop","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121607610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Heterogeneous partitioning in a workstation network","authors":"T. Schnekenburger, M. Huber","doi":"10.1109/HCW.1994.324959","DOIUrl":"https://doi.org/10.1109/HCW.1994.324959","url":null,"abstract":"We present several heterogeneous partitioning algorithms for parallel numerical applications. The goal is to adapt the partitioning to dynamic and unpredictable load changes on the nodes. The methods are based on existing homogeneous algorithms like orthogonal recursive bisection, parallel strips, and scattering. We apply these algorithms to a parallel numerical application in a network of heterogeneous workstations. The behavior of the individual methods in a system with dynamical load changes and heterogeneous nodes is investigated. In addition, the new methods are compared with the conventional methods for homogeneous partitioning.<<ETX>>","PeriodicalId":327341,"journal":{"name":"Proceedings Heterogeneous Computing Workshop","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123328834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamic task assignment in heterogeneous linear array networks for metacomputing","authors":"Sang-Young Cho, Kyu Ho Park","doi":"10.1109/HCW.1994.324960","DOIUrl":"https://doi.org/10.1109/HCW.1994.324960","url":null,"abstract":"In a heterogeneous computing system, the tasks of a program must be assigned to the heterogeneous machines so as to utilize the computational capabilities and resources of the system efficiently. This paper deals with a dynamic task assignment problem in heterogeneous computing systems, which permits each task to be relocated from machine to machine during the execution of a program. This problem is known to be NP-complete in the general case. In this paper, we extend the network-flow approach of C.-H. Lee, D. Lee and M. Kim (1992) to dynamic assignment for metacomputing. The dynamic assignment problem for a linear array network is first transformed into the network flow problem, and then solved by applying the Goldberg-Tarjan's (1988) network flow algorithm in time not worse than O(n/sup 2/m/sup 2spl phisup 2/ log nm/spl phi/), where n, m, and /spl phi/ are the numbers of machines, tasks, and phases of program execution, respectively.<<ETX>>","PeriodicalId":327341,"journal":{"name":"Proceedings Heterogeneous Computing Workshop","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114527967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Linguistic support for heterogeneous parallel processing: a survey and an approach","authors":"C. Weems, G. Weaver, S. Dropsho","doi":"10.1109/HCW.1994.324958","DOIUrl":"https://doi.org/10.1109/HCW.1994.324958","url":null,"abstract":"Coding a highly parallel application to run on a heterogeneous suite of processors (both metacomputers and mixed-mode computers) with high efficiency, ease of implementation, and portability is a significant challenge. The authors first survey recently proposed and existing parallel languages from the perspective of programming complex, heterogeneous systems. Thy then propose two essential features to he included in programming languages that are intended to support heterogeneity.<<ETX>>","PeriodicalId":327341,"journal":{"name":"Proceedings Heterogeneous Computing Workshop","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116574878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A heterogeneous processing (HP) framework for multimedia query processing","authors":"A. Khokhar, A. Ghafoor","doi":"10.1109/HCW.1994.324962","DOIUrl":"https://doi.org/10.1109/HCW.1994.324962","url":null,"abstract":"Defines a novel system based on a hierarchical computational and data abstraction model to handle multimedia queries involving face recognition, scene matching, and speech recognition. For this purpose, the system integrates the state-of-the-art research in diverse areas of the computational sciences, including parallel processing, computer vision and image processing, artificial intelligence, multimedia databases, and speech and signal processing. This system uses a heterogeneous processing framework consisting state-of-the-art image understanding and signal processing algorithms in addition to content-based retrieval techniques. These algorithms comprise of parallel coarse-grained (MIMD) symbolic and fine-grained (SIMD) numeric algorithms at various levels of this hierarchical model.<<ETX>>","PeriodicalId":327341,"journal":{"name":"Proceedings Heterogeneous Computing Workshop","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130840752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Matching and scheduling in a generalized optimal selection theory","authors":"B. Narahari, A. Youssef, Hyeong-Ah Choi","doi":"10.1109/HCW.1994.324969","DOIUrl":"https://doi.org/10.1109/HCW.1994.324969","url":null,"abstract":"Studies a model for matching and scheduling a task structure onto a heterogeneous suite of computers. The paper first generalizes optimal selection theory (OST) and its later augmentations to include general dependency graphs, which represent dependencies between subtasks, and presents the generalized OST (GOST) model. The GOST model allows nonoptimal choices of machines, as in augmented OST (AOST), and heterogeneous code blocks, as in heterogeneous OST (HOST), and incorporates communication time, system reconfiguration time, and data reformatting time (needed when data is exchanged between heterogeneous processors). Under the GOST model, we address the problem of matching/scheduling dependency graphs on a heterogeneous suite of computers. For arbitrary dependency graphs, matching/scheduling is NP-complete. But for the special instances of trees, and, more importantly, in the case of series-parallel dependency graphs we present polynomial time algorithms for optimal matching/scheduling.<<ETX>>","PeriodicalId":327341,"journal":{"name":"Proceedings Heterogeneous Computing Workshop","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129053312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}