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Managing Leakage Energy in Cache Hierarchies
- Journal of Instruction-level Parallelism
, 2003
"... Energy management is important for a spectrum of systems ranging from high-performance architectures to low-end mobile and embedded devices. With the increasing number of transistors, smaller feature sizes, lower supply and threshold voltages, the focus on energy optimization is shifting from dyn ..."
Abstract
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Cited by 3 (0 self)
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Energy management is important for a spectrum of systems ranging from high-performance architectures to low-end mobile and embedded devices. With the increasing number of transistors, smaller feature sizes, lower supply and threshold voltages, the focus on energy optimization is shifting from dynamic to leakage energy. In fact, leakage energy is projected to become the dominant portion of the chip power budget for 0.10 micron technology and below. Leakage energy is of particular concern in dense cache memories that form a major portion of the transistor budget.
Using Branch Prediction Information for Near-Optimal I-Cache Leakage
- Asia-Pacific Systems Architecture Conference, 2006
, 2006
"... This paper describes a new on-demand wakeup prediction policy for instruction cache leakage control that achieves better leakage savings than prior policies, and avoids the performance overheads of prior policies. The proposed policy reduces leakage energy by more than 92 % with only less than 0.3 % ..."
Abstract
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Cited by 2 (2 self)
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This paper describes a new on-demand wakeup prediction policy for instruction cache leakage control that achieves better leakage savings than prior policies, and avoids the performance overheads of prior policies. The proposed policy reduces leakage energy by more than 92 % with only less than 0.3 % performance overhead on average, whereas prior policies were either prone to severe performance overhead or failed to reduce the leakage energy as much. The key to this new on-demand policy is to use branch prediction information for the wakeup prediction. In the proposed policy, inserting an extra stage for wakeup between branch prediction and fetch, allows the branch predictor to be also used as a wakeup predictor without any additional hardware. Thus, the extra stage hides the wakeup penalty, not affecting branch prediction accuracy. Though extra pipeline stages typically add to branch misprediction penalty, in this case, the extra wakeup stage on the normal fetch path can be overlapped with misprediction recovery. With such consistently accurate wakeup prediction, all cache lines except the next expected cache line are in the leakage saving mode, minimizing leakage energy. We focus on super-drowsy leakage control using reduced supply voltage, because it is well suited to the instruction cache’s criticality. The proposed policy can be applied to other leakage saving circuit techniques as long as the wakeup penalty is at most one cycle. 1.
Reducing leakage in power-saving capable caches for embedded systems by using a filter cache
, 2007
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Reducing Leakage through Filter Cache
"... We evaluate the leakage reduction for both instruction and data cache in presence of drowsy or decay techniques. We discovered that a filter cache, traditionally used for reducing active power, can help reduce also leakage. The key idea is to reduce the lifetime of the lines that are in high-power s ..."
Abstract
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We evaluate the leakage reduction for both instruction and data cache in presence of drowsy or decay techniques. We discovered that a filter cache, traditionally used for reducing active power, can help reduce also leakage. The key idea is to reduce the lifetime of the lines that are in high-power state inside a leakage-saving cache. Power consumption has become one of the main concerns for designers, together with the performance. Caches account for the largest fraction of on-chip transistors in most modern processors. Therefore, they are a primary candidate for attacking the problem of the leakage. In average with the proposed solution, for instruction cache 24 % improvement in leakage savings and 1.5 % in IPC (Instruction Per Cycle) can be achieved with respect to drowsy cache. For data caches, 5 % and 5.4 % improvement can be achieved respectively. Experiments have been performed also with decay cache showing fewer benefits.

