IME’s Edge computing group partners with leading
industry partners, research institutes and local universities to foster
high-impact research based on three main pillars:
(1)Scalable SoC Architectures
(2)AI hardware, Near- and In-memory
weight hardware security
These focus areas are key to enabling Edge Computing
and the Internet of Things (
IoT). IME also
places deep emphasis on developing platform and IP portfolios for supporting
future computing technologies such as Neuromorphic Computing,
Analog-memory-based computation, Emerging memory devices, Deep Learning
hardware and Secure processors.
IME’s Edge Computing group has developed a suite of design techniques to realize an ultra-low-power SoC. These SoC are critical for power constrained IoT applications such as machine health monitoring, neural signal processing and tire monitoring. We are also working on thousand-core Neuromorphic and Deep Learning hardware to enable new generation of pattern learning and recognition based real-world applications. These includes mobile or wearable devices, smart sensors, computers, robots and autonomous vehicles.
(1) Tailored PE/Neuron behavior for different computation tasks
(2) Novel memory device and In-memory computing circuits for bandwidth boosting
(3) 2D and 3D large scale integration to minimize expensive off-chip communication
These techniques are developed within the framework of multiple multidisciplinary projects such as Neuromorphic Computing and Deep Learning Hardware.
and RF circuits are the
driving force and backbone for enabling 5G,
IoT, Autonomous Vehicles, Smart Cities,
various satellite communications applications.
IME’s mmwave & RF IC group is indigenously
formfactor mmwave radar & connectivity solutions with
antenna in package (
AiP) significantly for Industry by
collaborating with complementing research groups. The next generation Research
and development in MMICS & RFICs can be broadly classified into three
IME has developed far field wirelessly powered IoT nodes and demonstrated in a real life network scenario with simultaneous operation of sensing nodes. Employing various circuit deign techniques, IME’s portfolio of low power radio transceiver SoCs for sensor networks spans broad spectrum of applications and standards. Demonstrated capabilities include, low-power wireless for 2.4GHz Zigbee-like sensing node for watch like compact IoT node; 400MHz ARIB T67 radio for applications such as smart metering, remote control and health monitors, ultra-wideband (UWB) and sub-GHz custom radios. The team also has developed RF digital radio transceiver IP blocks for TV white space (TVWS) Wi-Fi bands, for smart factory, smart nation applications.
IME innovates circuit design processes for highly integrated cross-disciplinary technologies, using Smart IC Design platform. Using machine learning and circuit design, through this platform improves productivity. These are possible through rapid IP development and rapid design space exploration.
IME established technology platform and IP portfolio as the key enabling technology for high performance sensors, Internet of Things (IoT), smart wearables and integrated power regulators.
IME has demonstrated magnetic thin-film deposition and process integration methodology for embedding inductors in fan-out wafer level packaging (FOWLP). Its work on PMIC leverages the proven process integration methodology and focuses on thin-film magnetic inductor based integrated voltage regulator which can provide dynamic power delivery for power saving in mobile application processors and servers CPU. Some of its works include vibration energy harvester IC, wireless power receiver IC, and DC-DC converter with on-chip thin-film magnetic inductors. They are suitable for realizing integrated power management for IoT and wearable applications.
Targeted clinical applications include Neurology, Cardiology and Diabetes. IME already has an established circuit platform and IP portfolio, centred round Neuro-technology and Smart Wearables.