Computer Architecture Publications

• Azul: An Accelerator for Sparse Iterative Solvers Leveraging Distributed On-Chip Memory, Axel Feldmann, Courtney Golden, Yifan Yang, Joel S Emer, Daniel Sanchez, MICRO 2024 [paper]

• Spatula: A Hardware Accelerator for Sparse Matrix Factorization, Axel Feldmann, Daniel Sanchez, MICRO 2023 [paper]

• An Architecture to Accelerate Computation on Encrypted Data, Axel Feldmann*, Nikola Samardzic*, Aleksandar Krastev, Srinivas Devadas, Ronald Dreslinski, Christopher Peikert, Daniel Sanchez, IEEE Micro Top Picks 2022 [paper]

• CraterLake: A Hardware Accelerator for Efficient Unbounded Computation on Encrypted Data, Nikola Samardzic, Axel Feldmann, Aleksandar Krastev, Nathan Manohar, Nicholas Genise, Srinivas Devadas, Karim Eldefrawy, Christopher Peikert, Daniel Sanchez, ISCA 2022 [paper]

• F1: A fast and programmable accelerator for fully homomorphic encryption, Axel Feldmann*, Nikola Samardzic*, Aleksandar Krastev, Srini Devadas, Ron Dreslinski, Chris Peikert, and Daniel Sanchez, MICRO 2021 [paper]

• Livia: Data-centric computing throughout the memory hierarchy, Eliot Lockerman, Axel Feldmann, Mohammad Bakhshalipour, Alexandru Stanescu, Shashwat Gupta, Daniel Sanchez, and Nathan Beckmann, ASPLOS 2020 [paper]

GPU Programming Publications

Sometimes, I help friends write custom GPU kernels for their machine learning papers :)

• DsDm: Model-Aware Dataset Selection with Datamodels, Logan Engstrom, Axel Feldmann, Aleksander Mądry, ICML 2024 [paper]

• FeatUp: A Model-Agnostic Framework for Features at Any Resolution, Stephanie Fu*, Mark Hamilton*, Laura Brandt, Axel Feldmann, Zhoutong Zhang, William T. Freeman ICLR 2024 [paper]

• MiniFold: Simple, Fast, and Accurate Protein Structure Prediction, Jeremy Wohlwend, Mateo Reveiz, Matt McPartlon, Axel Feldmann, Wengong Jin, Regina Barzilay