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This paper will give an overview of multicore in automotive applications, covering the trends, benefits, challenges, and implementation scenarios. The automotive silicon industry has been building multicore and multiprocessor systems for a long time. The reasons for this choice have been: increased performance, safety redundancy, increased I/O & peripheral, access to multiple architectures (performance type e.g. DSP) and technologies. In the past, multiprocessors have been mainly considered as multi-die, multi-package with simple interconnection such as serial or parallel busses with possible shared memories. The new challenge is to implement a multicore, micro-processor that combines two or more independent processors into a single package, often a single integrated circuit (IC). The multicores allow a computing device to exhibit some form of thread-level parallelism (TLP).

Machine learning systems are gaining acceptance in the fields of inferential sensing, mechatronic control and prognostics. However, software implementations can place excessive demands on the ECU, and so real-time classification rates are not always possible. This paper describes the integration of a hardware implementation of a machine learning algorithm into a comprehensive hardware and software prototyping environment for powertrain applications. The paper describes the hardware and software architectures developed, provides an overview of the new methodologies necessary to access the power of the machine learning system, and illustrates its application in the powertrain control field

With the ever increasing amount of available software processing resources in a vehicle, more and more high-level algorithms are emerging to improve the existing systems in a car. Often these algorithms only need a platform with a bus connection and some resources such as processing power and memory space. These functions are predestined to be integrated into existing systems that have free resources. This paper will examine the role of time protection in these multi-algorithm systems and describe what timing protection means and why it is required. The processing time will be partitioned to the different processing levels like interrupts, services and tasks. The problems of timing protection will be illustrated as well as its limitations. The conflict between real-time requirements and timing protection will be shown. Finally Autosar will be examined with focus on timing protection and applicability in actual development projects.