- System stack performance optimization of HPC and Cloud systems.
- Heterogeneous cloud (GPU/FPGA based datacenters) scheduling and orchestration.
- Serverless computing provider and user side challenges.
Mobile and IoT systems:
- Improving energy efficiency of video processing in mobile systems.
- Hardware-Software co-optimizations in Mobile CPUs.
- Performance and energy-efficient designs on Internet of Things (IoT) systems.
Manycore architectures and GPUs:
- Designing high performance energy-efficient heterogeneous GPU architectures.
- Compiler-assisted optimization on manycore platforms.
- Minimizing data movement in Near Data Computing.
Hardware efficient Machine Learning:
- Optimizing system hierarchy for emerging Machine Learning and Deep learning applications.
- Minimizing computations across Deep Learning frameworks for energy efficiency in CPUs.
- Exploring compute accelerators (GPUs, FPGAs) for Deep Learning application.
- Power-efficient neuromorphic computing systems.
- Simulation of Spiking neural networks.