The Horizon 2020 MANGO project aims at exploring deeply heterogeneous accelerators for use in High-Performance Computing systems running multiple applications with different Quality of Service (QoS) levels. The main goal of the project is to exploit customization to adapt computing resources to reach the desired QoS. For this purpose, it explores different but interrelated mechanisms across the architecture and system software. In particular, in this paper we focus on the runtime resource management, the thermal management, and support provided for parallel programming, as well as introducing three applications on which the project foreground will be validated.

Transistor miniaturization, combined with the dawn of novel switching semiconductor structures, calls for careful examination of the variability and aging of the computer fabric. Time-zero and time-dependent phenomena need to be carefully considered so that the dependability of digital systems can be guaranteed. Already, architectures contain many mechanisms that detect and correct physically induced reliability violations. In many cases, guarantees on functional correctness come at a quantifiable performance cost. The current paper discusses the FP7-612069-HARPA project of the European Commission and its approach towards dependable performance. This project provides solutions for performance variability mitigation, under the run time presence of fabric variability/aging and built-in reliability, availability and serviceability (RAS) techniques. In this paper, we briefly present and discuss modeling and mitigation techniques developed within HARPA, covering many abstractions of digital system design: from the transistor to the application layer.