Towards General Purpose Acceleration by Exploiting Common Data-Dependence Forms. - Vidushi Dadu; Jian Weng 002; Sihao Liu; Tony Nowatzki (MICRO, 2019)

DAEGEN: A Modular Compiler for Exploring Decoupled Spatial Accelerators. - Jian Weng 002; Sihao Liu; Vidushi Dadu; Tony Nowatzki (IEEE Comput. Archit. Lett., 2019)

Exploiting Fine-Grain Ordered Parallelism in Dense Matrix Algorithms. - Jian Weng 002; Vidushi Dadu; Tony Nowatzki (CoRR, 2019)

A Hybrid Systolic-Dataflow Architecture for Inductive Matrix Algorithms. - Jian Weng 002; Sihao Liu; Zhengrong Wang; Vidushi Dadu; Tony Nowatzki (HPCA, 2020)

DSAGEN: Synthesizing Programmable Spatial Accelerators. - Jian Weng 002; Sihao Liu; Vidushi Dadu; Zhengrong Wang; Preyas Shah; Tony Nowatzki (ISCA, 2020)

Towards General-Purpose Acceleration: Finding Structure in Irregularity. - Vidushi Dadu; Jian Weng 002; Sihao Liu; Tony Nowatzki (IEEE Micro, 2020)

PolyGraph: Exposing the Value of Flexibility for Graph Processing Accelerators. - Vidushi Dadu; Sihao Liu; Tony Nowatzki (ISCA, 2021)

TaskStream: accelerating task-parallel workloads by recovering program structure. - Vidushi Dadu; Tony Nowatzki (ASPLOS, 2022)

Generalizing Programmable Accelerators for Irregularity - Vidushi Dadu (2022)

Profiling Hyperscale Big Data Processing. - Abraham Gonzalez; Aasheesh Kolli; Samira Manabi Khan; Sihang Liu 001; Vidushi Dadu; Sagar Karandikar; Jichuan Chang; Krste Asanovic; Parthasarathy Ranganathan (ISCA, 2023)

RAGO: Systematic Performance Optimization for Retrieval-Augmented Generation Serving. - Wenqi Jiang 001; Suvinay Subramanian; Cat Graves; Gustavo Alonso; Amir Yazdanbakhsh; Vidushi Dadu (ISCA, 2025)

Concorde: Fast and Accurate CPU Performance Modeling with Compositional Analytical-ML Fusion. - Arash Nasr-Esfahany; Mohammad Alizadeh; Victor Lee; Hanna Alam; Brett W. Coon; David E. Culler; Vidushi Dadu; Martin Dixon; Henry M. Levy; Santosh Pandey; Parthasarathy Ranganathan; Amir Yazdanbakhsh (ISCA, 2025)