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212 M.Y. Qadri, D. Matichard, and K.D. McDonald Maier profile with deadlines. The benchmark records the time consumed in calculating individual data points, and reports the miss of deadlines. The benchmark is scalable to theoretically any number of cores and could be used as a tool to measure an operating system’s scheduling characteristics. This paper is divided into five sections. The following section overviews the related work in the area of embedded benchmarking, section 3 and 4 detail the proposed benchmark characteristics, and results based on a multicore architecture. Finally the last section forms the conclusion. 2 Related Work With the current drive towards multicore platforms, standard APIs like OpenMP, POSIX [3] and Message Passing Interface (MPI) [4] have facilitated the development of multicore threaded applications. Multicore platforms have been widely applied in the real-time systems to achieve higher throughput and lower power consumption. The embedded system community has long been using non-embedded benchmarks such as SPEC [5], Whetstone [6], Dhrystone [7] and NAS parallel benchmarks [8], to evaluate the performance of the target systems. A limited number of benchmarks are specifically designed for the embedded system evaluation. One of the few embedded system specific benchmark suites is the Embedded Microprocessor Benchmark Consortium (EEMBC) benchmark tools suite comprising of algorithms and applications targeting telecommunication, networking, automotive, and industrial products. A recent addition of a so called MultiBench [9] suite has realized the performance evaluation of shared memory symmetric multicore processors. These benchmarks could be targeted to any platform supporting POSIX thread library, and are delivered as customizable set of workloads, each comprising of one or more work items. Although computationally rich and extensive the benchmarks by no means provide real time performance statistics of the system, and for such applications EEMBC has two applications in a separate single core benchmark suite called AutoBench [10]. This benchmark suite comprises of real time applications such as ‘Angle to Time Conversion’ and ‘Tooth to Spark’ [11]. The Angle to Time Conversion application simulates an embedded automotive application, where the processor measures the real-time delay between pulses sensed from the gear on the crankshaft. Then it calculates the Top Dead Center (TDC) position on the crankshaft, computes the engine speed, and converts the tooth wheel pulses to crankshaft angle position. The Tooth-to-Spark application simulates an automotive application that processes air/fuel mixture and ignition timing in real-time. Another real-time single core embedded benchmark is PapaBench [12], that is based on a unmanned aerial vehicle (UAV) control software for AVR and ARM microcontroller systems. The benchmark provides the worst case execution time computation which is useful for systems scheduling analysis. Guthaus et al. [13] presented the MiBench embedded benchmark suite. This benchmark suite is a single core, non real-time implementation of 35 applications in the areas such as automotive/industrial, consumer, office, network, security, and telecommunication. As all of the above mentioned benchmarks either are not using threaded implementation or are not real-time applications, a more specific benchmark suite addressing the two issues altogether is developed by Express Logic
JetBench: An Open Source Real-Time Multiprocessor Benchmark 213 Inc., i.e. the so called ‘Thread-Metric’ benchmark suite [14]. The tool is specifically designed to measure a real-time operating system’s (RTOS) capability to handle a threaded application. The benchmark is not a multiprocessor implementation as the thread model executes in a round-robin fashion and is useful to explore real-time context switching and memory management capabilities of an RTOS. The related research in the embedded benchmarking area is pointing to the need of a more specific multicore real-time benchmark suite, capable to instrument performance characteristics of shared memory architectures. The following section introduces and overviews the JetBench benchmark application, an Open-Source tool for realtime, multiprocessor embedded architectures. 3 Benchmark Characteristics The JetBench application is composed of thermodynamic calculations based on three types of jet engines, i.e. 1) TurboJet, 2) Turbojet with afterburner, and 3) a Turbofan engine (See Fig. 1). The application contains parameters specific to the said models as described in the NASA’s EngineSim application [15]. The benchmark allows a user defined input flight profile to be simulated containing speed, altitude, throttle, and deadline time, while in response to that, the processing time for various thermodynamic calculations is monitored and reported (See Fig. 2). Fig. 1. Three different Jet Models used in JetBench (Adapted from [15]) An overview of the thermodynamic calculations used in the benchmark application is given in Appendix. Fig. 2. JetBench Application I/O Parameters
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Lecture Notes in Computer Science 5
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Volume Editors Christian Müller-Sc
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General Chair Organization Christia
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Organization IX Hartmut Schmeck Kar
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Keynote Table of Contents HyVM - Hy
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Table of Contents XIII JetBench:AnO
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130 M. Kayaalp et al. INSTRUCTION 1
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