Indian Institute of Technology Gandhinagar

The Stanford University Unstructured design is a tool for solving multi-disciplinary problems governed by the Partial Differential Equations on general, unstructured grids. The Overset algorithm ‘Overset Parallel Engine for AeRodynamic Applications’ developed at Institute of High Performance Computing, Singapore allows dynamic overset grid capabilities with any number of bodies using parallel processing. This paper presents the coupling of OPERA with SU2 for complex multi- body aerospace problems. The modified software suite is tested for the flow past a three dimensional sphere. The results compared with analytical results support the potential and working of the algorithm compared to a non-overlapping grid. The same problem is analyzed for moving overlapping grid. The velocity contours at different time instance are shown and are found to be continuous across the overlapping grid.

Carbon Capture and Storage (CCS) is crucial for reducing emissions in hard-to-decarbonize sectors such as cement, steel, and power generation. For India, heavily reliant on coal, CCS provides a means to lower emissions while maintaining energy security. While global CCS deployment has gained momentum through policy support and funding, high costs remain a significant challenge. In India, basalt formations, especially in the Deccan Traps, present a promising and cost-effective option for CO2 storage through mineralization. India's CCS policy is still in development, with short-term incentives like carbon credits and potential long-term goals, such as carbon taxes, being considered. To scale CCS, India requires robust funding mechanisms, technological innovation, and large-scale CCS clusters. International collaboration and investment will be essential in addressing financial and technological barriers. With the right infrastructure, research, and policy framework, CCS can become a key component of India's strategy to meet its net-zero target by 2070.

We examine the feasibility of using synthetic medical data generated by GANs in the classroom, to teach data science in health informatics. We present an end-to-end methodology to retain instructional utility, while preserving privacy to a level, which meets regulatory requirements: (1) a GAN is trained by a certified medical-data security-aware agent, inside a secure environment; (2) the final GAN model is used outside of the secure environment by external users (instructors or researchers) to generate synthetic data. This second step facilitates data handling for external users, by avoiding de-identification, which may require special user training, be costly, and/or cause loss of data fidelity. We benchmark our proposed GAN versus various baseline methods using a novel set of metrics. At equal levels of privacy and utility, GANs provide small footprint models, meeting the desired specifications of our application domain. Data, code, and a challenge that we organized for educational purposes are available.

The architecture of main memory has experienced a paradigm shift in recent years, with non volatile memory technologies (NVM) like Phase Change Memory (PCM) being incorporated into the hierarchy at the same level as DRAM. This transformation is being carried out by either splitting the memory address across two or more memory technologies, or using a faster technology with higher lifetimes, typically the DRAM, as a cache for the higher capacity, albeit slower main memory made up of a NVM. Design of such hybrid architectures remains an active area of research from the perspective of DRAM-as-a-cache design, since DRAM could quickly become the bottleneck, as cache lookups require multiple accesses for reading tag and data. In this paper, we augment the DRAM-as-a-cache model with a novel DRAM cache prefetcher that builds on state of the art Alloy Cache. The new DRAM cache architecture allows for prefetching data at both cacheline and page granularities from the NVM, and as a result, provides upto a maximum of 2× performance improvement over a state of the art baseline.