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Concept
Memory access pattern
Summary
In computing, a memory access pattern or IO access pattern is the pattern with which a system or program reads and writes memory on secondary storage. These patterns differ in the level of locality of reference and drastically affect cache performance, and also have implications for the approach to parallelism and distribution of workload in shared memory systems. Further, cache coherency issues can affect multiprocessor performance, which means that certain memory access patterns place a ceiling on parallelism (which manycore approaches seek to break).
Computer memory is usually described as "random access", but traversals by software will still exhibit patterns that can be exploited for efficiency. Various tools exist to help system designers and programmers understand, analyse and improve the memory access pattern, including VTune and Vectorization Advisor, including tools to address GPU memory access patterns
Memory access patterns also have implications for security, which motivates some to try and disguise a program's activity for privacy reasons.
Sequential access
The simplest extreme is the sequential access pattern, where data is read, processed, and written out with straightforward incremented/decremented addressing. These access patterns are highly amenable to prefetching.
Strided or simple 2D, 3D access patterns (e.g., stepping through multi-dimensional arrays) are similarly easy to predict, and are found in implementations of linear algebra algorithms and . Loop tiling is an effective approach. Some systems with DMA provided a strided mode for transferring data between subtile of larger 2D arrays and scratchpad memory.
A linear access pattern is closely related to "strided", where a memory address may be computed from a linear combination of some index. Stepping through indices sequentially with a linear pattern yields strided access. A linear access pattern for writes (with any access pattern for non-overlapping reads) may guarantee that an algorithm can be parallelised, which is exploited in systems supporting compute kernels.
Official source
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