Sriram Krishnamoorthy

Sriram Krishnamoorthy is a Research Professor at Washington State University's School of Electrical Engineering & Computer Science and a research scientist at Pacific Northwest National Laboratory (PNNL), where he serves as the System Software and Applications Team Leader in PNNL's High Performance Computing group.

Dr. Krishnamoorthy earned his B.E. from the College of Engineering, Guindy in Chennai, India, and his M.S. and Ph.D. degrees from The Ohio State University. He is a senior member of the Institute of Electrical and Electronics Engineers.

His research focuses on parallel programming models, fault tolerance, and compile-time/runtime optimizations for high-performance computing. He has made significant contributions in areas including:

• Fault tolerance techniques that minimize rollback during failures
• Dynamic load balancing for irregular parallel applications
• Compiler and runtime optimizations for HPC applications
• GPU programming and heterogeneous computing
• Quantum chemistry simulations and quantum computing

Dr. Krishnamoorthy's publications span computational science, high-performance computing, and quantum chemistry. His recent work shows strong trends toward quantum computing applications, fault tolerance in large-scale systems, and optimization of computational chemistry methods. He has developed techniques for density matrix quantum circuit simulation, floating-point error analysis, and scalable execution of coupled-cluster models.

His scientific achievements have been recognized with several prestigious awards:

• Best Paper Award at International Conference on High Performance Computing (HiPC'03)
• Best Paper Award at International Parallel and Distributed Processing Symposium (IPDPS'04)
• U.S. Department of Energy Early Career award (2013)
• PNNL's Ronald L. Brodzinski Award for Early Career Exceptional Achievement (2013)
• The Ohio State University's Outstanding Researcher award (2008)

Dr. Krishnamoorthy has advised numerous graduate students and collaborated extensively with researchers across computational science domains. His work on the NWChem project demonstrates significant grant funding and large-scale collaborative research efforts in computational chemistry.

He leads research efforts in PNNL's High Performance Computing group, focusing on system software and applications development for next-generation supercomputing platforms.