HiPEAC

Sohan Lal

Sohan Lal is a junior professor and head of the Massively Parallel Systems Group at Hamburg University of Technology (TUHH). Before joining TUHH, he was a postdoctoral researcher at the Technical University of Berlin (TU Berlin), working on a DFG-funded research project on advanced modeling and runtime support for large-scale HPC clusters (Celerity). He graduated with a Ph.D. in Computer Science from TU Berlin in August 2019. His dissertation was titled “Power Modeling and Architectural Techniques for Energy-Efficient GPUs” and was supervised by Prof. Ben Juurlink. At TU Berlin, he worked on two EU-funded research projects on low power parallel computing on GPUs (LPGPU), where he led several tasks, collaborated with consortium members to deliver joint deliverables and contributed significantly to their success. His Ph.D. dissertation work was also conducted in the context of LPGPU projects. For his dissertation, he investigated bottlenecks that cause low performance and low energy efficiency in GPUs and proposed architectural techniques to improve performance and energy efficiency. The dissertation results were published in several reputed conferences such as IPDPS, DATE, and ISPASS. He won several grants such as HiPEAC travel grants, and a HiPEAC collaboration grant to visit Prof. Henk Coporaal (TU/e) which led to a joint publication at DATE. He was a semifinalist at ACM SRC held at MICRO'18. He is interested in computer architecture in general and graphics processing unit (GPU) architecture in particular. His broad research interests include power and performance modeling, parallel systems, memory systems, heterogeneous computing, approximate computing, applied machine learning, and GPU security.

Before Ph.D., he received his masters from the Indian Institute of Technology Delhi (IITD) in 2011. Before that, he worked as a Lecturer at Shri Mata Vaishno Devi University (SMVDU), which was his first teaching stint that made him deeply passionate and excited about teaching and mentorship. He also worked as an IT specialist in the Government of India. He received his bachelor in Computer Science and Engineering from Government College of Engineering and Technology (GCET), Jammu, India in 2003.


Expertise areas

Topics: Accelerators, Approximate computing, Computer architecture, CPUs, Embedded Systems, Energy efficiency / Low-power computing, GPUs, High-performance computing, Machine learning, Memory, Multicore / Manycore, Parallel computing