Bounds on Memory Bandwidth in Streamed Computations

Abstract

The growing disparity between processor and memory speeds has caused memory bandwidth to become the performance bottleneck for many applications. In particular, this performance gap severely impacts stream-orientated computations such as (de)compression, encryption, text searching, and scientific (vector) processing. This paper looks at streaming computations and derives analytic upper bounds on the bandwidth attainable from a class of access reordering schemes. We compare these bounds to the simulated performance of a particular dynamic access ordering scheme, the Stream Memory Controller (SMC). We are building the SMC, and where possible we relate our analytic bounds and simulation data to the simulation performance of the hardware. The results suggest that the SMC can deliver nearly the full attainable bandwidth with relatively modest hardware costs.