In this paper, SIMD and MIMD solutions
Abstract-This paper proposes a SIMD solution to air traffic control (ATC) using an enhanced SIMD machine model called an Associative Processor (AP). This differs from previous ATC systems that are designed for MIMD computers and have a great deal of difficulty meeting the predictability requirements for ATC, which are critical for meeting the strict certification standards required for safety critical software components. The proposed SIMD solution will support accurate and meaningful predictions of worst case execution times and will guarantee all deadlines are met. Also, the software will be much simpler and smaller in size than the current corresponding ATC software. An important consequence of these features is that the V&V (Validation and Verification) process will be considerably simpler than for current ATC software. Additionally, the associative processor is enhanced SIMD hardware and is considerably cheaper and simpler than the MIMD hardware currently used to support ATC. The ClearSpeed CSX600 accelerator is used to emulate the AP model. A preliminary implementation of the proposed method has been developed and experimental results comparing MIMD and CSX600 approaches are presented. The performance of CSX600 has better scalability, efficiency, and predictability than that of MIMD.
Abstract-This paper proposes a solution to air traffic control (ATC) using an enhanced SIMD machine model called an Associative Processor (AP). Our solution differs from previous ATC systems that are designed for MIMD computers and have a great deal of difficulty meeting the predictability requirements for ATC, which are critical for meeting the strict certification standards required for safety critical software components. The proposed AP solution supports accurate predictions of worst case execution times and guarantees all deadlines are met. Furthermore, the software developed based on the AP model is much simpler and smaller in size than the current corresponding ATC software. As the associative processor is built from SIMD hardware, it is considerably cheaper and simpler than the MIMD hardware currently used to support ATC. We have designed a prototype for eight ATC real-time tasks on ClearSpeed CSX600 accelerator that is used to emulate AP. Performance is evaluated in terms of execution time and predictability and is compared to the fastest host-only version implemented using OpenMP on an 8-core multiprocessor (MIMD). Our extensive experiments show that the AP implementation meets all deadlines that can be statically scheduled. To the contrary, some tasks miss their deadlines when implemented on MIMD. It is shown that the proposed AP solution will support accurate and meaningful predictions of worst case execution times and will guarantee that all deadlines are met.
This paper has two complementary focuses. The first is the system design and algorithmic development for air traffic control (ATC) using an associative SIMD processor (AP). The second is the comparison of this implementation with a multiprocessor implementation and the implications of these comparisons. This paper demonstrates how one application, ATC, can more easily, more simply, and more efficiently be implemented on an AP than is generally possible on other types of traditional hardware. The AP implementation of ATC will take advantage of its deterministic hardware to use static scheduling. The software will be dramatically smaller and cheaper to create and maintain. Likewise, a large AP system will be considerably simpler and cheaper than the MIMD hardware currently used. While APs were used for ATC-type applications earlier, these are no longer available. We use a ClearSpeed CSX600 accelerator to emulate the AP solutions of ATC on an ATC prototype consisting of eight data-intensive ATC real-time tasks. Its performance is compared with an 8-core multiprocessor (MP) using OpenMP. Our extensive experiments show that the AP implementation meets all deadlines while the MP will regularly miss a large number of deadlines. The AP code will be similar in size to sequential code for the same tasks and will avoid all of the additional support software needed with an MP to handle dynamic scheduling, load balancing, shared resource management, race conditions, * Corresponding author Email addresses: myuan@cs.kent.edu (Man(Mike) Yuan), jbaker@cs.kent.edu (Johnnie W. Baker), wllcm@att.net (Will C. Meilander) 1 This is the first author footnote. Preprint submitted to Journal of Parallel and Distributed Computing August 15, 2012false sharing, etc. At this point, essentially only MIMD systems are built. Many of the advantages of using an AP to solve an ATC problem would carry over to other applications. AP solutions for a wide variety of applications will be cited in this paper. Applications that involve a high degree of data parallelism such as database management, text processing, image processing, graph processing, bioinformatics, weather modeling, managing UAS (Unmanned Aircraft Systems or drones) etc, are good candidates for AP solutions. This raises the issue of whether we should routinely consider using non-multiprocessor hardware like the AP for applications where substantially simpler software solutions will normally exist. It also raises the question of whether the use of both AP and MIMD hardware in the same system could provide more versatility and efficiency. Either the AP or MIMD could serve as the primary system but could hand off jobs it could not handle efficiently to the other system.
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