Hybrid Cloud & AI

Technological innovations in hybrid cloud and artificial intelligence aim to expand the potential of edge computing and cloud security capabilities across public and private clouds. As the high-performance computing needs of global society ramp up, the ability to access curated data and processing power from multiple distributed data centers and workloads will be paramount.

With an emphasis on data protection and isolation, IBM and Illinois teams will collaborate to explore how open-source innovation and artificial intelligence can drive the next era of cloud computing, and define the essential workforce skills necessary for running increasingly powerful and critical workloads.

Current Research Projects

Illinois Faculty IBM Technical Leads Topics
Jabbarvand, Reyhaneh Saurabh Sinha  Advancing Code Translation and Validation Through Neuro-Symbolic Approaches
Adve, Vikram; Wang, Yuxiong;  David P. Grove  Sound Code Creation Using Program Synthesis and Language Models
Gupta, Indranil;  Alagappan, Ramnatthan; Ganesan, Aishwarya; Xu, Tianyin; McHenry, Kenton; Marini, Luigi Jha, Saurabh; Schwartz, Larisa; Narayanaswami, Chandra;  Carlos Costa HDC: A Full-Stack Solution for the Hybrid Cloud Marrying Data and compute
Nagi, Rakesh Chen Wang Hybrid AI/ML-Optimization Approaches to Cloud Native Workflow Scheduling
Nahrstedt, Klara; Chen, Deming; Huang, Jian Tamar Eilam; Eun Lee; Asser Tantawi; Alaa Youssef; Pradip Bose; Nandhini Chandramoorthy; Carlos Costa Sustainable AI Hybrid Cloud Systems Powered by Renewable Energy and
Smart Grid
Kale, Laxmikant; Kindratenko, Vlad; Carlos Costa Claudia Misale; Sara Kokkila-Schumacher; Pedro David Bello-Maldonado  Frameworks for Cloud-based Parallel Applications Supporting Runtime Adaptivity and Resource Elasticity
Kalbarczyk, Zbigniew; Iyer, Ravishankar; Basar, Tamer Chen Wang; Hubertus Franke; Saurabh Jha  SLO-oriented Energy Cost Optimization with Multi-tiered Machine Learning
Torrellas, Josep; Xu, Tianyin Hubertus Franke  High-performance and Energy-efficient Platform Support of Serverless Environments for general purpose and ML Applications
Iyer, Ravishankar K. Chandra Narayanaswami  ResiliANT AIOps: Foundation-model Driven Resilience for Cloud Computing 
Adve, Sarita; Godfrey, Brighten; Wang, Shenlong Mudhakar Srivatsa; Pradip Bose Codesigned Distributed Inference Architectures for Immersive Computing
Misailovic, Sasa; Adve, Vikram;  Prasanth Chatarasi; Swagath Venkataramani; Vijayalaksmi Srinivasan Felix: Gradient-Based Compiler Optimization of Tensor Programs
Kim, Nam Sung; Huang, Jian; Mittal, Radhika;  Seetharami Seelam Holistic Networking, Storage and GPU Management and Acceleration Co-design for AI Training Supercomputers
Xu, Tianyin Hubertus Franke A Safe and Expressive Infrastructure for OS Kernel Extensions
Wang, Gang; Levchenko, Kirill Gheorghe Almasi; Hubertus Franke Scalable Continuous Remote Attestation for Multi-Cloud
Chen, Deming Sandhya Koteshwara; Mengmei Ye; Hubertus Franke Confidential Computing with Heterogenous Accelerators in Hybrid Clouds

Click here to see completed projects