Software-Distributed Shared Memory over Heterogeneous Micro-server Architecture

Nowadays, the design of computing architectures not only targets computing performances but also the energy power savings. Low-power computing units, such as ARM and FPGA-based nodes, are now being integrated together with high-end processors and GPGPU accelerators into computing clusters. One example is the micro-server architecture that consists of a backbone onto which it is possible to plug computing nodes. These nodes can host high-end and low-end CPUs, GPUs, FPGAs and multi-purpose accelerators such as manycores, building up a real heterogeneous platform. In this context, there is no hardware to federate memories, and the programmability of such architectures suddenly relies on the developer experience to manage data location and task communications. The purpose of this paper is to evaluate the possibility of bringing back the convenient shared-memory programming model by deploying a software-distributed shared memory among heterogeneous computing nodes. We describe how we have built such a system over a message-passing runtime. Experimentations have been conducted using a parallel image processing application over an homogeneous cluster and an heterogeneous micro-server.