Updates on the Low-Level Abstraction of Memory Access

TL;DR

The paper discusses recent enhancements to the LLAMA C++ library, which provides a zero-overhead abstraction for flexible, efficient memory layout management across heterogeneous hardware architectures, focusing on multidimensional structured data.

Contribution

It introduces new features and improvements to the LLAMA library, enabling compile-time array extents, computation during memory access, and explicit SIMD support for better performance and flexibility.

Findings

Enhanced support for compile-time array extents

Added computation capabilities during memory access

Introduced explicit SIMD support

Abstract

Choosing the best memory layout for each hardware architecture is increasingly important as more and more programs become memory bound. For portable codes that run across heterogeneous hardware architectures, the choice of the memory layout for data structures is ideally decoupled from the rest of a program. The low-level abstraction of memory access (LLAMA) is a C++ library that provides a zero-runtime-overhead abstraction layer, underneath which memory mappings can be freely exchanged to customize data layouts, memory access and access instrumentation, focusing on multidimensional arrays of nested, structured data. After its scientific debut, several improvements and extensions have been added to LLAMA. This includes compile-time array extents for zero-memory-overhead views, support for computations during memory access, new mappings for bit-packing, switching types, byte-splitting, memory access instrumentation, and explicit SIMD support. This contribution provides an overview of recent developments in the LLAMA library.