Kailash Prasad / Tools & expertise

Tools & expertise

AI hardware, approximate arithmetic, SRAM design, digital implementation, and tools for circuit and architectural exploration.

AI hardware

Arithmetic & accelerator design

Approximate adders, multipliers, and dividers; posit number representations; and hardware–software codesign for DNN accelerators. Evaluating energy, performance, area, and application accuracy alongside storage and data-transfer requirements.

Approximate computingPosit arithmeticHardware–software codesign
Compute research
01 / Memory circuits

SRAM design & characterization

Memory cells, peripheral circuits, sense amplifiers, and memory subsystems. Circuit sizing and simulation with a focus on performance, energy, and reliable operation.

Cadence VirtuosoLiberateCalibreAbstract
02 / Digital implementation

RTL to GDS

Experience across logic design, simulation, synthesis, and physical implementation, including two team tapeouts in UMC 65 nm.

Design CompilerGenusVCSNCSIMInnovusXilinx Vivado
03 / Automation

Programming & design tools

Building simulators, automating EDA workflows, and exploring design spaces through scripting and custom tools.

PythonVerilogSystemVerilogCTclBashMATLAB
04 / People & practice

Leadership & mentorship

Led teams of around 15 students for tapeouts in 2020 and 2022. Mentored more than 70 students and published research with more than 15 student collaborators.

Academic collaborations
05 / Devices & embedded systems

From device physics to hardware

Compact modelling and TCAD experience, alongside embedded platforms used in teaching and prototyping.

Sentaurus TCADKeil µVisionRaspberry PiArduinoAVRArm Cortex-M0Arm78085
06 / Foundations

Coursework & research grounding

VLSI and asynchronous circuit design, transistor physics, computer architecture, analog IC design, microfabrication, machine learning, computer vision, computer networking, and two-dimensional materials.

Teaching resources