Aasish Kumar Sharma
Biography
Aasish is a scientific employee under Julian Kunkel and is interested in performance optimization, big data analysis, data science and computer vision using advanced technologies such as parallel and high-performance computing, as well as, quantum computing.
ResearchGate
Research Interests
- Optimization
- High-Performance Computing
- Data Science
Teaching
Open Thesis Topics
A survey on Machine Learning Approaches on Optimization of Workload Mapping Problem in Heterogeneous HPC LandscapeApply
1) Theory: To explore and present "Efficient ML Workload Mapping Techniques" in Heterogeneous HPC Landscape 2) Practical: Data collection and showing an optimize workflow based on a sample workload.
A survey on Machine Learning Approaches on Optimization of Workload Scheduling Problem in Heterogeneous HPC LandscapeApply
1) Theory: To explore and present "Efficient ML Workload Scheduling Techniques" in Heterogeneous HPC Landscape 2) Practical: Data collection and showing an optimize workflow based on a sample workload.
Theoretical Analysis of Mapping Problem Using Quantum ApproachApply
1) Theory: To explore and present how HPC resource mapping problem can be solved using Quantum Approach 2) Practical: To prepare a toy model with a use case of HPC workload and show an try your approach to see the result.
Theses
- Performance Analysis of Convolutional Neural Network Applying Quantum Annealing, Aasish Kumar Sharma (Master's Thesis), Advisors: Sanjeeb Prasad Pandey, 2020-12-30, BibTeX URL
Publications
2024
- HOSHMAND: Accelerated AI-Driven Scheduler Emulating Conventional Task Distribution Techniques for Cloud Workloads (Michael Bidollahkhani, Aasish Kumar Sharma, Julian Kunkel), IEEE Computers, Software, and Applications Conference, pp. 1-8, IEEE, IEEE, COMPSAC 2024, 2024-07 BibTeX
All publications as BibTex