Projects
Reliable and Scalable Quantum Computing
Students: Narges Alavisamani, Suhas Vittal
Quantum computing offers exponential speedups for certain key problems, but realizing this requires large-scale quantum systems. Quantum computers are highly error-prone, necessitating robust error correction methods. As computer architects, we address the system design challenges for scalability and reliability in quantum computing.
Efficient AI
Students: Anish Saxena
Contemporary AI models, such as Large Language Models (LLMs), stress the memory system, leading to increasingly high resource consumption, energy costs, and yet low efficiency. We explore ways to tackle the GPU memory wall to improve the serving efficiency of LLMs, reducing data movement while increasing throughput, and lowering the carbon footprint of AI.
Secure Hardware Design
Students: Anish Saxena, Hritvik Taneja
Hardware is an emerging source of vulnerability for attacks threatening data confidentiality and integrity. Numerous attacks have emerged targeting different layers of the hardware stack such as processors (Spectre, Meltdown, and others), caches (side-channel attacks) and main-memories (cold-boot, rowhammer, and other physical attacks), that are capable of either leaking or tampering sensitive data. One of the biggest challenges we address in this project is how to redesign hardware to be secure against current and future attacks, while keeping the cost of security minimal. At the same time, we leverage learnings from secure hardware design to discover new faster and stealthier attacks.