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Universal Numerical Encoder and Profiler Reduces Computing's Memory Wall with Software, FPGA, and SoC Implementations

Published 20 Mar 2013 in cs.OH | (1303.4994v1)

Abstract: In the multicore era, the time to computational results is increasingly determined by how quickly operands are accessed by cores, rather than by the speed of computation per operand. From high-performance computing (HPC) to mobile application processors, low multicore utilization rates result from the slowness of accessing off-chip operands, i.e. the memory wall. The APplication AXcelerator (APAX) universal numerical encoder reduces computing's memory wall by compressing numerical operands (integers and floats), thereby decreasing CPU access time by 3:1 to 10:1 as operands stream between memory and cores. APAX encodes numbers using a low-complexity algorithm designed both for time series sensor data and for multi-dimensional data, including images. APAX encoding parameters are determined by a profiler that quantifies the uncertainty inherent in numerical datasets and recommends encoding parameters reflecting this uncertainty. Compatible software, FPGA, and systemon-chip (SoC) implementations efficiently support encoding rates between 150 MByte/sec and 1.5 GByte/sec at low power. On 25 integer and floating-point datasets, we achieved encoding rates between 3:1 and 10:1, with average correlation of 0.999959, while accelerating computational "time to results."

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