Author
Krishna M. Kavi
Other affiliations: University of Alabama in Huntsville, University of Texas at Austin, University of Texas at Arlington ...read more
Bio: Krishna M. Kavi is an academic researcher from University of North Texas. The author has contributed to research in topics: Cache & Dataflow. The author has an hindex of 20, co-authored 150 publications receiving 1750 citations. Previous affiliations of Krishna M. Kavi include University of Alabama in Huntsville & University of Texas at Austin.
Topics: Cache, Dataflow, Dataflow architecture, Cache pollution, CPU cache
Papers published on a yearly basis
Papers
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01 Apr 1995
TL;DR: This book discusses how to schedule the processes among processing elements to achieve the expected performance goals, such as minimizing execution time, minimizing communication delays, or maximizing resource utilization.
Abstract: Advances in hardware and software technologies have led to an increased interest in the use of large-scale parallel and distributed systems for database, real-time, defense, and large-scale commercial applications. One of the biggest system issues is developing effective techniques for the distribution of multiple program processes on multiple processors. This book discusses how to schedule the processes among processing elements to achieve the expected performance goals, such as minimizing execution time, minimizing communication delays, or maximizing resource utilization.
403 citations
TL;DR: The results show that SDF architecture can outperform the superscalar and scales better with the number of functional units and allows for a good exploitation of Thread Level Parallelism (TLP) and available chip area.
Abstract: In this paper, the scheduled dataflow (SDF) architecture-a decoupled memory/execution, multithreaded architecture using nonblocking threads-is presented in detail and evaluated against superscalar architecture. Recent focus in the field of new processor architectures is mainly on VLIW (e.g., IA-64), superscalar, and superspeculative designs. This trend allows for better performance, but at the expense of increased hardware complexity and, possibly, higher power expenditures resulting from dynamic instruction scheduling. Our research deviates from this trend by exploring a simpler, yet powerful execution paradigm that is based on dataflow and multithreading. A program is partitioned into nonblocking execution threads. In addition, all memory accesses are decoupled from the thread's execution. Data is preloaded into the thread's context (registers) and all results are poststored after the completion of the thread's execution. While multithreading and decoupling are possible with control-flow architectures, SDF makes it easier to coordinate the memory accesses and execution of a thread, as well as eliminate unnecessary dependencies among instructions. We have compared the execution cycles required for programs on SDF with the execution cycles required by programs on SimpleScalar (a superscalar simulator) by considering the essential aspects of these architectures in order to have a fair comparison. The results show that SDF architecture can outperform the superscalar. SDF performance scales better with the number of functional units and allows for a good exploitation of Thread Level Parallelism (TLP) and available chip area.
83 citations
TL;DR: This paper proposes a new algorithm that uses multiple scheduling strategies for efficient non-preemptive scheduling of tasks, known as group-EDF (gEDF), based on dynamic grouping of tasks with deadlines that are very close to each other, and using Shortest Job First technique to schedule tasks within the group.
68 citations
TL;DR: It is found that current object-oriented languages that have concurrency features are often compromised in important areas, including inheritance capability, efficiency, ease of use, and degree of parallel activity.
Abstract: Fourteen concurrent object-oriented languages are compared in terms of how they deal with communication, synchronization, process management, inheritance, and implementation trade-offs. The ways in which they divide responsibility between the programmer, the compiler, and the operating system are also investigated. It is found that current object-oriented languages that have concurrency features are often compromised in important areas, including inheritance capability, efficiency, ease of use, and degree of parallel activity. Frequently, this is because the concurrency features were added after the language was designed. The languages discussed are Actors, Abd/1, Abd/R, Argus, COOL, Concurrent Smalltalk, Eiffel, Emerald, ES-Kit C++, Hybrid, Nexus, Parmacs, POOL-T, and Presto. >
59 citations
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TL;DR: In this article, the authors discuss aeronautical engineering and safety engineering, and propose a framework for safety engineering in aeronautic engineering and aerospace engineering, which is discussed in detail.
Abstract: This article discusses aeronautical engineering and safety engineering.
58 citations
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TL;DR: It is proved that, with appropriate bounds on node density and intracluster and intercluster transmission ranges, HEED can asymptotically almost surely guarantee connectivity of clustered networks.
Abstract: Topology control in a sensor network balances load on sensor nodes and increases network scalability and lifetime. Clustering sensor nodes is an effective topology control approach. We propose a novel distributed clustering approach for long-lived ad hoc sensor networks. Our proposed approach does not make any assumptions about the presence of infrastructure or about node capabilities, other than the availability of multiple power levels in sensor nodes. We present a protocol, HEED (Hybrid Energy-Efficient Distributed clustering), that periodically selects cluster heads according to a hybrid of the node residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED terminates in O(1) iterations, incurs low message overhead, and achieves fairly uniform cluster head distribution across the network. We prove that, with appropriate bounds on node density and intracluster and intercluster transmission ranges, HEED can asymptotically almost surely guarantee connectivity of clustered networks. Simulation results demonstrate that our proposed approach is effective in prolonging the network lifetime and supporting scalable data aggregation.
4,889 citations
TL;DR: A taxonomy that classifies 27 scheduling algorithms and their functionalities into different categories is proposed, with each algorithm explained through an easy-to-understand description followed by an illustrative example to demonstrate its operation.
Abstract: Static scheduling of a program represented by a directed task graph on a multiprocessor system to minimize the program completion time is a well-known problem in parallel processing. Since finding an optimal schedule is an NP-complete problem in general, researchers have resorted to devising efficient heuristics. A plethora of heuristics have been proposed based on a wide spectrum of techniques, including branch-and-bound, integer-programming, searching, graph-theory, randomization, genetic algorithms, and evolutionary methods. The objective of this survey is to describe various scheduling algorithms and their functionalities in a contrasting fashion as well as examine their relative merits in terms of performance and time-complexity. Since these algorithms are based on diverse assumptions, they differ in their functionalities, and hence are difficult to describe in a unified context. We propose a taxonomy that classifies these algorithms into different categories. We consider 27 scheduling algorithms, with each algorithm explained through an easy-to-understand description followed by an illustrative example to demonstrate its operation. We also outline some of the novel and promising optimization approaches and current research trends in the area. Finally, we give an overview of the software tools that provide scheduling/mapping functionalities.
1,373 citations
07 Mar 2004
TL;DR: A protocol is presented, HEED (hybrid energy-efficient distributed clustering), that periodically selects cluster heads according to a hybrid of their residual energy and a secondary parameter, such as node proximity to its neighbors or node degree, which outperforms weight-based clustering protocols in terms of several cluster characteristics.
Abstract: Prolonged network lifetime, scalability, and load balancing are important requirements for many ad-hoc sensor network applications. Clustering sensor nodes is an effective technique for achieving these goals. In this work, we propose a new energy-efficient approach for clustering nodes in ad-hoc sensor networks. Based on this approach, we present a protocol, HEED (hybrid energy-efficient distributed clustering), that periodically selects cluster heads according to a hybrid of their residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED does not make any assumptions about the distribution or density of nodes, or about node capabilities, e.g., location-awareness. The clustering process terminates in O(1) iterations, and does not depend on the network topology or size. The protocol incurs low overhead in terms of processing cycles and messages exchanged. It also achieves fairly uniform cluster head distribution across the network. A careful selection of the secondary clustering parameter can balance load among cluster heads. Our simulation results demonstrate that HEED outperforms weight-based clustering protocols in terms of several cluster characteristics. We also apply our approach to a simple application to demonstrate its effectiveness in prolonging the network lifetime and supporting data aggregation.
1,373 citations
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01 Apr 1998
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586 citations