Low-power, high-performance analog neural branch prediction. - Renée St. Amant; Daniel A. Jiménez; Doug Burger (MICRO, 2008)

Mixed-Signal Approximate Computation: A Neural Predictor Case Study. - Renée St. Amant; Daniel A. Jiménez; Doug Burger (IEEE Micro, 2009)

Dark Silicon and the End of Multicore Scaling. - Hadi Esmaeilzadeh; Emily R. Blem; Renée St. Amant; Karthikeyan Sankaralingam; Doug Burger (IEEE Micro, 2012)

Power Limitations and Dark Silicon Challenge the Future of Multicore. - Hadi Esmaeilzadeh; Emily R. Blem; Renée St. Amant; Karthikeyan Sankaralingam; Doug Burger (ACM Trans. Comput. Syst., 2012)

Power challenges may end the multicore era. - Hadi Esmaeilzadeh; Emily R. Blem; Renée St. Amant; Karthikeyan Sankaralingam; Doug Burger (Commun. ACM, 2013)

Multicore Model from Abstract Single Core Inputs. - Emily R. Blem; Hadi Esmaeilzadeh; Renée St. Amant; Karthikeyan Sankaralingam; Doug Burger (IEEE Comput. Archit. Lett., 2013)

General-purpose code acceleration with limited-precision analog computation. - Renée St. Amant; Amir Yazdanbakhsh; Jongse Park; Bradley Thwaites; Hadi Esmaeilzadeh; Arjang Hassibi; Luis Ceze; Doug Burger (ISCA, 2014)

Lean Attention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers. - Rya Sanovar; Srikant Bharadwaj; Renée St. Amant; Victor Rühle; Saravan Rajmohan (CoRR, 2024)

Ensuring Fair LLM Serving Amid Diverse Applications. - Redwan Ibne Seraj Khan; Kunal Jain; Haiying Shen; Ankur Mallick; Anjaly Parayil; Anoop Kulkarni; Steve Kofsky; Pankhuri Choudhary; Renée St. Amant; Rujia Wang; Yue Cheng 001; Ali Raza Butt; et al. (CoRR, 2024)

Serving Models, Fast and Slow:Optimizing Heterogeneous LLM Inferencing Workloads at Scale. - Shashwat Jaiswal; Kunal Jain; Yogesh Simmhan; Anjaly Parayil; Ankur Mallick; Rujia Wang; Renée St. Amant; Chetan Bansal; Victor Rühle; Anoop Kulkarni; Steve Kofsky; Saravan Rajmohan (CoRR, 2025)