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As the size of Deep Neural Networks (DNNs) continues to grow to increase accuracy and solve more complex problems, their energy footprint also scales. Weight pruning reduces DNN model size and the computation by removing redundant weights. However, we implemented weight pruning for several popular networks on a variety of hardware platforms and observed surprising results. For many networks, the network...
Heterogeneous multicore systems are composed of multiple cores with varying energy and performance characteristics. A controller dynamically detects phase changes in applications and migrates execution onto the most efficient core that meets the performance requirements. In this paper, we show that existing techniques that react to performance changes break down at fine-grain intervals, as performance...
Heterogeneous multicore systems—comprising multiple cores with varying performance and energy characteristics—have emerged as a promising approach to increasing energy efficiency. Such systems reduce energy consumption by identifying application phases and migrating execution to the most efficient core that meets performance requirements. However, the overheads of migrating between cores limit opportunities...
InOrder (InO) cores achieve limited performance because their inability to dynamically reorder instructions prevents them from exploiting Instruction-Level-Parallelis Conversely, Out-of-Order (OoO) cores achieve high performance by aggressively speculating past stalled instructions and creating highly optimized issue schedules. It has been observed that these issue schedules tend to repeat for sequences...
Heterogeneous architectures offer many potential avenues for improving energy efficiency in today's low-power cores. Two common approaches are dynamic voltage/frequency scaling (DVFS) and heterogeneous microarchitectures (HMs). Traditionally both approaches have incurred large switching overheads, which limit their applicability to coarse-grain program phases. However, recent research has demonstrated...
Heterogeneous multicore systems -- comprised of multiple cores with varying capabilities, performance, and energy characteristics -- have emerged as a promising approach to increasing energy efficiency. Such systems reduce energy consumption by identifying phase changes in an application and migrating execution to the most efficient core that meets its current performance requirements. However, due...
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