NEMA GPU-WEAR is a novel platform to develop and implement ultra-low power, heterogeneous, multicore Graphics Processing Unit (GPU) technology, for SoCs (System on the Chip). The platform is designed, to extend battery life by decreasing the power-consumption by an order of magnitude for the next generation of mobile, wearable and embedded devices while running fast, graphically rich display and 4K video applications.

Dealing with the levels of power consumption required by wearables1 and Internet of Things (IoT) devices represents a major technological challenge that demands novel multi-disciplinary approaches spanning circuit, architecture, compiler, and API level optimization techniques. The main challenge in these new devices is the battery life and how to extend it to more than one day without having to search for wall plugs and charging stations. Thus, ultra‐low power devices performing energy‐conscious graphics calculations are urgently needed in the market. GPU‐WEAR is designed to further refine and fully validate the first heterogeneous multicore embedded graphics processing unit (GPU), the associated low‐power software library, and the run‐time system explicitly optimized for the ultra‐low power requirements posed by the wearables and the IoT market.

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The envisaged heterogeneous GPU includes two different types of general purpose (GP)‐GPU cores with different microarchitectures, regarding for example the number of registers or hardware threads. The unique selling point of the project’s output is that both core types are enabled by a single and disruptive low‐power Instruction Set Architecture (ISA), thus relying on a single executable and software/compiler toolchain.

In addition, GPU‐WEAR will release an integrated software environment, in the form of a Software Development Kit (SDK), referred to as GPU‐WEAR‐SDK, to streamline the development process for hardware, low‐power, compiler, device driver, software, and application engineers. Thus, GPU‐WEAR‐SDK will drastically reduce the design cycle and time‐to‐market of related products. In particular, it will be used during the pre‐sales process for technology validation and will enable the customization/optimization of the innovative heterogeneous GPU for different application domains, e.g. computational photography and augmented reality. The latter characteristic is crucial for the fast‐growing and fast‐evolving IoT market. As such, GPU‐WEAR contributes directly to worldwide economic and societal challenges associated with efficient powering of wearable devices.