Bandwidth-Based Performance Tuning and Prediction
Chen Ding and Ken Kennedy
ABSTRACT
As the speed gap widens between CPU and memory, memory hierarchy
performance has become the bottleneck for most applications. This is
due in part to the difficulty of fully utilizing the deep and complex
memory hierarchies found on most modern machines. In the past,
various tools on performance tuning and prediction have been developed
to improve machine utilization. However, these tools are not
effective in practice because they either do not consider memory
hierarchy or do so with expensive and machine-specific program
simulations. In this paper, we first demonstrate that application
performance is now primarily limited by memory bandwidth. With this
observation, we describe a new approach based on estimating and
monitoring memory bandwidth consumption, which can achieve accurate
and efficient performance tuning and prediction. When evaluated on a
3000-line benchmark program, NAS/SP , the bandwidth-based method
has enabled a user to obtain a speedup of 1.19 by inspecting and
tuning only 5\% of the source code. Furthermore its compile-time
prediction of overall execution time was within 10\% of the actual
running time.
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