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The increased complexity of today’s industrial embedded systems stands in need for more computational power while most systems must adhere to a restricted energy consumption, either to prolong the battery lifetime or to reduce operational costs. The many-core processor is therefore a natural ﬁt. Due to the simple architecture of the compute cores, and therefore their good analyzability, such processors are additionally well suited for real-time applications. In our research, we focus on two particular problems which need to be addressed in order to pave the way into the many-core era. The ﬁrst area is power and thermal aware execution frameworks, where we present different energy aware extensions to well known load balancing algorithms, allowing them to dynamically scale the number of active cores depending on their workload. In contrast, an additional framework is presented which balances workloads to minimize temperature gradients on the die. The second line of works focuses on industrial standards in the face of massively parallel platforms, where we address the automotive and automation domain. We present an execution framework for IEC 61131-3 applications, allowing the consolidation of several IEC 61131-3 applications on the same platform. Additionally, we discuss several architectural options for the AUTOSAR software architecture on such massively parallel platforms.