Wordwidth, instructions, looping, and virtualization: the role of sharing in absolute energy minimization

A. DeHon
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引用次数: 2

Abstract

When are FPGAs more energy efficient than processors? This question is complicated by technology factors and the wide range of application characteristics that can be exploited to minimize energy. Using a wire-dominated energy model to estimate the absolute energy required for programmable computations, we determine when spatially organized programmable computations (FPGAs) require less energy than temporally organized programmable computations (processors). The point of crossover will depend on the metal layers available, the locality, the SIMD wordwidth regularity, and the compactness of the instructions. When the Rent Exponent, p, is less than 0.7, the spatial design is always more energy efficient. When p=0.8, the technology offers 8-metal layers for routing, and data can be organized into 16b words and processed in tight loops of no more than 128 instructions, the temporal design uses less energy when the number of LUTs is greater than 64K. We further show that heterogeneous multicontext architectures can use even less energy than the p=0.8, 16b word temporal case.
字宽、指令、循环和虚拟化:共享在绝对能量最小化中的作用
fpga何时比处理器更节能?这个问题由于技术因素和广泛的应用特性而变得复杂,这些特性可以用来最大限度地减少能源。使用线主导的能量模型来估计可编程计算所需的绝对能量,我们确定何时空间组织的可编程计算(fpga)比时间组织的可编程计算(处理器)需要更少的能量。交叉点将取决于可用的金属层、局部性、SIMD字宽规则性和指令的紧凑性。当租金指数p < 0.7时,空间设计更节能。当p=0.8时,该技术提供8个金属层用于路由,数据可以组织成16b个字,并在不超过128条指令的紧密环路中进行处理,当lut数量大于64K时,时序设计使用更少的能量。我们进一步表明,异构多上下文架构使用的能量甚至比p=0.8, 16b单词时态的情况更少。
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