A Two-Layer Component-Based Allocation for Embedded Systems with GPUs

TL;DR

This paper proposes a two-layer component-based allocation approach for heterogeneous CPU-GPU embedded systems to reduce complexity and improve allocation efficiency, demonstrated on an underwater robot system.

Contribution

It introduces a novel 2-layer architecture that abstracts GPU details to simplify component-to-hardware allocation in embedded systems.

Findings

Reduced allocation complexity compared to traditional methods

Effective allocation scheme demonstrated on an underwater robot

Abstracted GPU information improves scalability and manageability

Abstract

Component-based development is a software engineering paradigm that can facilitate the construction of embedded systems and tackle its complexities. The modern embedded systems have more and more demanding requirements. One way to cope with such versatile and growing set of requirements is to employ heterogeneous processing power, i.e., CPU-GPU architectures. The new CPU-GPU embedded boards deliver an increased performance but also introduce additional complexity and challenges. In this work, we address the component-to-hardware allocation for CPU-GPU embedded systems. The allocation for such systems is much complex due to the increased amount of GPU-related information. For example, while in traditional embedded systems the allocation mechanism may consider only the CPU memory usage of components to find an appropriate allocation scheme, in heterogeneous systems, the GPU memory usage needs also to be taken into account in the allocation process. This paper aims at decreasing the component-to-hardware allocation complexity by introducing a 2-layer component-based architecture for heterogeneous embedded systems. The detailed CPU-GPU information of the system is abstracted at a high-layer by compacting connected components into single units that behave as regular components. The allocator, based on the compacted information received from the high-level layer, computes, with a decreased complexity, feasible allocation schemes. In the last part of the paper, the 2-layer allocation method is evaluated using an existing embedded system demonstrator; namely, an underwater robot.