Low-Level Abstraction of Memory Access

LLAMA is a cross-platform C++17 template header-only library for the abstraction of memory access patterns. It distinguishes between the view of the algorithm on the memory and the real layout in the background. This enables performance portability for multicore, manycore and gpu applications with the very same code.

In contrast to many other solutions LLAMA can define nested data structures of arbitrary depths. It is not limited to struct of array and array of struct data layouts but also capable to explicitly define memory layouts with padding, blocking, striding or any other run time or compile time access pattern.

To achieve this goal LLAMA is split into mostly independent, orthogonal parts completely written in modern C++17 to run on as many architectures and with as many compilers as possible while still supporting extensions needed e.g. to run on GPU or other many core hardware.

Further information:

https://github.com/alpaka-group/llama
video recording (from 00:40 min onwards) and slides of a May 2021 Compute Accelerator Forum presentation

Reference:

B. M. Gruber, G. Amadio, J. Blomer, A. Matthes, R. Widera, M. Bussmann (2021). LLAMA: The Low-Level Abstraction For Memory Access. arxiv.org/abs/2106.04284