Why Some Like It Loud: Timing Power Attacks in Multi-tenant Data Centers Using an Acoustic Side Channel. - Mohammad A. Islam 001; Luting Yang; Kiran Ranganath; Shaolei Ren (Proc. ACM Meas. Anal. Comput. Syst., 2018)

Speeding up Collective Communications Through Inter-GPU Re-Routing. - Kiran Ranganath; AmirAli Abdolrashidi; Shuaiwen Leon Song; Daniel Wong 001 (IEEE Comput. Archit. Lett., 2019)

LC-MEMENTO: A Memory Model for Accelerated Architectures. - Kiran Ranganath; Jesun Firoz; Joshua Suetterlein; Joseph B. Manzano; Andres Marquez; Mark Raugas; Daniel Wong 001 (LCPC, 2021)

Energy Efficient Task Graph Execution Using Compute Unit Masking in GPUs. - Marcus Chow; Kiran Ranganath; Robert Lerias; Mika Shanela Carodan; Daniel Wong 001 (RSDHA@SC, 2021)

MAPA: multi-accelerator pattern allocation policy for multi-tenant GPU servers. - Kiran Ranganath; Joshua D. Suetterlein; Joseph B. Manzano; Shuaiwen Leon Song; Daniel Wong 001 (SC, 2021)

RDARuntime: An OS for AI Accelerators. - Benjamin Glick; Arjun Sabnis; Renate Kempf; Arnav Goel; Aarti Lalwani; Guoyao Feng; Kiran Ranganath (SC Workshops, 2023)

Toward a Holistic Performance Evaluation of Large Language Models Across Diverse AI Accelerators. - Murali Emani; Sam Foreman; Varuni Sastry; Zhen Xie; Siddhisanket Raskar; William Arnold; Rajeev Thakur; Venkatram Vishwanath; Michael E. Papka; Sanjif Shanmugavelu; Darshan Gandhi; Hengyu Zhao; et al. (IPDPS (Workshops), 2024)