Programming languages that provide multidimensional arrays and a flat linear model of memory must implement a mapping between these two domains to order array elements in memory. This layout function is fixed at language definition time and constitutes an invisible, non-programmable array attribute. In reality, modern memory systems are architecturally hierarchical rather than flat, with substantial differences in performance among different levels of the hierarchy. This mismatch between the model and the true architecture of memory systems can result in low locality of reference and poor performance. Some of this loss in performance can be recovered by re-ordering computations using transformations such as loop tiling. We explore nonlinear array layout functions as an additional means of improving locality of reference. For a benchmark suite composed of dense matrix kernels, we show by timing and simulation that two specific layouts (4D and Morton) have low implementation costs (2-5% of total running time) and high performance benefits (reducing execution time by factors of 1.1-2.5); that they have smooth performance curves, both across a wide range of problem sizes and over representative cache architectures; and that recursion-based control structures may be needed to fully exploit their potential.
In general, collaboration infrastructures have supported sharing of an object based on its logical structure. However, current implementations assume an implicit binding between this logical structure and particular system-defined abstractions. We present a new composable design based on programming patterns that eliminates this binding, thereby increasing the range of supported objects and supporting extensibility.
Given the widespread deployment of cyber-physical systems and their safety-critical nature, reliability and security guarantees offered by such systems are of paramount importance. While the security of such systems against sensor attacks have garnered significant attention from researchers in recent times, improving the reliability of a control software implementation against transient environmental disturbances need to be investigated further. Scalable formal methods for verification of actual control performance guarantee offered by software implementations of control laws in the face of sensory faults have been explored in recent work [20]. However, the formal verification of the improvement of system reliability by incorporating sensor fault mitigation techniques like Kalman filtering [29] and sensor fusion [18, 52] remains to be explored. Moreover, system designers face complex tradeoff choices for deciding upon the usage of fault and attack mitigation techniques and scheduling them on available system resources as they incur extra computation load. In the present work, our contributions are threefold. We formally analyze the actual performance guarantee of control software implementations enabled with additional fault mitigation techniques. We consider task-level models of such implementations enabled with security and fault tolerance primitives and construct a timed automata-based model which checks for schedulability on heterogeneous multi-core platforms. We leverage these methodologies in the context of a novel Design-Space-Exploration (DSE) framework that considers target reliability and security guarantees for a control system and computes schedulable design options while considering well-known platform-level security improvement and fault mitigation techniques. We validate our contributions over several case studies from the automotive domain.
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