Edge Computing

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 computing

(3)Ultra-light 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.  

Scalable SoC Architectures
Practical workloads on edge devices have a wide spectrum, from nW-scale, always-on sensor node to high performance deep-inference network on autonomous vehicle. To accommodate this, IME investigates heavily on silicon fabric and RISC-V based scalable SoC architecture.

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. 

AI hardware, Near-and In-memory computing
Ubiquitous machine learning tasks on edge require unorthodox architectures to support enormous data flow and neural-net computation work loads. IME’s Edge Computing group deploys a holistic approach to enable true intelligent on edge: 

(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.

Ultra-light weight hardware security
The number of IoT devices is exploding at 17% CAGR towards 75B devices in 2025. Protecting the integrity and privacy of these IoT devices is a huge concern, not only for research community but also general public and the industry. To enable widespread deployment of IoT for smart nation, IME’ Edge Computing group is working on an end-to-end solution to safeguard users’ sensitive data. This is built on top of a trusted, intelligent silicon using SCA-resilient IPs, ultra-light weight ciphers and highly random entropy sources.
RF mmWave

mmWave and RF circuits are the driving force and backbone for enabling 5G, IoT, Autonomous Vehicles, Smart Cities, Healthcare monitoring, Contactless sensing and various satellite communications applications. IME’s mmwave & RF IC group is indigenously developing low 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 categories:

  High Resolution mmWave Radar
Applications that IME is developing are high resolution hybrid beam forming radars for automotive (ADAS Cars), drone applications and satellite radar applications. The MMICs are developed in CMOS, SiGe or III-V technology platforms depending on the application needs. Working with sub-system and DSP partners, mmwave radar is being customised with unique features for futuristic applications like contactless heart rate and breath rate monitoring, warehouse stock monitoring, non-destructive testing (NDT) applications  such as crack detection, imaging and many more. 
  mmWave Connectivity
At IME we 
are developing MMIC solutions for last mile and front haul connectivity for cellular applications like 5G and 6G, and SOTM. Scalable phased arrays with indigenously developed MMICs with antenna in package (AiP) are being developed  for these applications bringing the whole form factor, cost down drastically while also reducing the reflective losses due to mmWave  transitions and dissipation due to the long feeding network to the antenna outside the chip.
   
Radios for Low Power, Battery-less, Cognitive Connectivity

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.

 Smart IC Design
Modern electronic integrated circuits (ICs) are strictly designed to deliver operational and functional specifications. Designing these ICs involve the use of electronic design automation (EDA) software. A typical IC design process goes through a series of complex steps and trial-and-error to achieve design goals, thus slowing down productivity in the process. The motivation for increasing productivity in effective ways have shifted from improving the EDA tools and their interoperability, to designing faster and greater varieties of IC intellectual property (IP), which is becoming more aligned with overall business strategies.

 

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.

 

 ULP Analog & Mixed-Signal IC
Analog and mixed-signal circuits build the bridge between the analog and digital domains. IME’s Ultra-low-power (ULP) Analog and Mixed-signal IC group focus on the low voltage, ultra-low-power analog and mixed-signal integrated circuit development with three main focus areas:
(1)Sensor Interface IC
(2)Biomedical IC
(3)Power Management

 

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. 

Power Management

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.

Biomedical Integrated Circuits
IME’s Biomedical ICs group research focuses on low-voltage, low-power integrated circuits design for wearable and implantable medical devices. IME collaborates with local and overseas clinical partners and leading biomedical device companies to develop cutting edge technologies for unmet clinical needs. Key circuit design capabilities include;
1)high fidelity sensor readout circuits,
2)high efficiency actuator driving circuits,
3)energy harvesting
4)bio-signal processors.

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.

Sensor Interface IC
IME’s sensor interface IC design IPs build on special circuit techniques of continuous time ∆∑ modulation based charge balancing and voltage-controlled oscillator (VCO) based digitization. Some of its works include high resolution accelerometer readout system-on-chip (SoC) for industrial applications such as vibration sensing and inertial navigation, ultra-low power capacitive, resistive, potentiostat, and biopotential readout ICs for sensing pressure, current and voltage in biomedical and industrial applications. These readout ICs can be coupled with direct digital interface for wireless sensor node (WSN) targeting IoT applications.