Workload Dependent Mitigation Approaches For Performance Variability
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Workload Dependent Mitigation Approaches for Performance Variability
This book provides a holistic view of workload-dependent mitigation techniques for performance variability. The authors describe the use of design-time profiling information to reduce the uncertainties in future execution time calculation at run time, thereby offering the best option for minimizing system costs while reducing missed deadlines. Readers are introduced to an approach that combines dynamic voltage and frequency scaling (DVFS) with heterogeneous datapaths (HDP), enabling users to tackle performance variability of multiple timescales down to the sub-millisecond level.
Neuromorphic Solutions for Sensor Fusion and Continual Learning Systems
This book provides novel theoretical foundations and experimental demonstrations of Spiking Neural Networks (SNNs) in tasks such as radar gesture recognition for IoT devices and autonomous drone navigation using a fusion of retina-inspired event-based camera and radar sensing. The authors describe important new findings about the Spike-Timing-Dependent Plasticity (STDP) learning rule, which is widely believed to be one of the key learning mechanisms taking place in the brain. Readers will be enabled to create novel classes of edge AI and robotics applications, using highly energy- and area-efficient SNNs
Workload Dependent Mitigation Approaches for Performance Variability
This book provides a holistic view of workload-dependent mitigation techniques for performance variability. The authors describe the use of design-time profiling information to reduce the uncertainties in future execution time calculation at run time, thereby offering the best option for minimizing system costs while reducing missed deadlines. Readers are introduced to an approach that combines dynamic voltage and frequency scaling (DVFS) with heterogeneous datapaths (HDP), enabling users to tackle performance variability of multiple timescales down to the sub-millisecond level.