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Power and Failure Analysis of CAM Cells Due to Process Variations

Process variations arise due to processing and masking limitations, and result in random or spatially varying deviation from the designed parameter values. Changes in these parameters cause electrical parameters to vary, such as effective channel length and threshold voltage. These mismatches modify the strength of individual devices resulting in various failures. In this paper, we present a failure analysis of CAM cells under process variation in 32-nm CMOS technology. We investigate the effects of variations in Leff and Vt on the performance and power consumption of CAM cells.

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Designing Memory Subsystems Resilient to Process Variations

As technology scales, more sophisticated fabrication processes cause variations in many different parameters in the device. These variations could severely affect the performance of processors by making the latency of circuits less predictable and thus requiring conservative design approaches. In this paper, we use Monte-Carlo simulations in addition to worst-case circuit analysis to establish the overall delay due to process variations in a cache subsystem under both typical and worst-case conditions.

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Synchronization Coherence: A Transparent Hardware Mechanism for Cache Coherence and Fine-Grained Synchronization

The quest to improve performance forces designers to explore finer-grained multiprocessor machines. Ever increasing chip densities based on CMOS improvements fuel research in highly parallel chip multiprocessors with 100s of processing elements. With such increasing levels of parallelism, synchronization is set to become a major performance bottleneck and efficient support for synchronization an important design criterion.

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Energy-Efficient Hardware Data Prefetching

Extensive research has been done in prefetching techniques that hide memory latency in microprocessors leading to performance improvements. However, the energy aspect of prefetching is relatively unknown. While aggressive prefetching techniques often help to improve performance, they increase energy consumption by as much as 30% in the memory system. This paper provides a detailed evaluation on the energy impact of hardware data prefetching and then presents a set of new energy-aware techniques to overcome prefetching energy overhead of such schemes.

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