Simon Cook

LLVM has a great track record for being able to target a large range of processors, both large 32/64-bit devices and deeply embedded 8/16-bit processors. From most perspectives, from Clang through to code generation, the size of most operations do not make much difference to the ease of implementation. However there are some assumptions that are baked deeply into the compiler; one of which is the memory access width, more specifically that it is addressible in 8-bit words. This however is not always the case, many embedded DSPs can only access memory with 16-bit addressibility, and trying to teach LLVM about this proves to be a challenge.

In this talk, we will present our first explorations in this area, and share our thoughts on how we can make LLVM more memory agnostic for all targets with non-8-bit memory.

An Altruistic Processor (AAP) is an open hardware 16-bit architecture for deeply embedded applications running on small FPGA devices. It is somewhat configurable, with a minimum of 4 16-bit general registers, at least one word-addressed code space of up to 16Mword and at least one byte addressed data space of up to 64kbyte.

A key part of any implementation of an embedded toolchain is a simulator of the architecture, both such that user written code can be run and so the compiler's implementation itself can be verified. As part of AAP, we have implemented a simulator based on LLVM MC that both runs standalone and as part of a gdb/lldbserver.

In this talk I will discuss the design and my experiences of using LLVM as the host for a simulator.

MAGEEC, a collaboration between the open source software house, Embecosm, and Bristol University's microcomputer group, aims to use machine learning to improve the energy efficiency of compiled code. This entirely open source project is funded by the UK government through the Technology Strategy Board, and aims to provide working systems based on LLVM and GCC by the end of 2014.

Bring along your applications and have their energy consumption measured on a pre-instrumented Arduino, Raspberry Pi or BeagleBone. Alternatively, bring along your own design on a breadboard and we'll hook up a PowerSense shield to measure the energy usage.

Other people: Andrew Back Jeremy Bennett Kerstin Eder Simon Hollis James Pallister