Accelerating Simulation-based Inference with Emerging AI Hardware. - Sourabh Kulkarni; Alexander Tsyplikhin; Mario Michael Krell; Csaba Andras Moritz (ICRC, 2020)

NanoBatch DPSGD: Exploring Differentially Private learning on ImageNet with low batch sizes on the IPU. - Edward H. Lee; Mario Michael Krell; Alexander Tsyplikhin; Victoria Rege; Errol Colak; Kristen W. Yeom (CoRR, 2021)

Time-series ML-regression on Graphcore IPU-M2000 and Nvidia A100. - Jan Balewski; Zhenying Liu; Alexander Tsyplikhin; Manuel Lopez Roland; Kristofer E. Bouchard (PMBS@SC, 2022)

A Comprehensive Evaluation of Novel AI Accelerators for Deep Learning Workloads. - Murali Emani; Zhen Xie; Siddhisanket Raskar; Varuni Sastry; William Arnold; Bruce Wilson; Rajeev Thakur; Venkatram Vishwanath; Zhengchun Liu; Michael E. Papka; Cindy Orozco Bohorquez; Rick Weisner; et al. (PMBS@SC, 2022)

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)