Publications

[C1] Z. Li*, S. Ghodrati*, A. Yazdanbakhsh*, H. Esmaeilzadeh, M. Kang, "Accelerating Attention through Gradient-Based Learned Runtime Pruning," in IEEE/ACM International Symposium on Computer Architecture (ISCA), 2022 (Acceptance Rate = 16%). (* stands for equal contribution.)

[C2] H. Esmaeilzadeh, S. Ghodrati, J. Gu, S. Guo, A. B. Kahng, J. K. Kim, S. Kinzer, R. Mahapatra, S. D. Manasi, E. Mascarenhas, S. S. Sapatnekar, R. Varadarajan, Z. Wang, H. Xu, B. R. Yatham, Z. Zeng , "VeriGOOD-ML: An Open-Source Flow for Automated ML Hardware Synthesis," in IEEE/ACM International Conference on Computer Aided Design (ICCAD), 2021.

[W1] S. Ghodrati, H. Esmaeilzadeh, "Multi-Tenancy: The Next Step in DNN Acceleration," in Workshop on Architecture, Compiler, and System Support for Multi-model DNN Workloads, MICRO, 2021.

[C3] S. Kinzer, J. Kim, S. Ghodrati, B. Yatham, A. Althoff, D. Mahajan, S. Lerner, H. Esmaeilzadeh, "A Computational Stack for Cross-Domain Acceleration," in IEEE International Symposium on High Performance Computer Architecture (HPCA), 2021 (Acceptance Rate = 24%).

[C4] S. Ghodrati, B. Ahn, J. Kim, S. Kinzer, B. Yatham, N. Alla, H. Sharma, M. Alian, E. Ebrahimi, N.S. Kim, C. Young, H. Esmaeilzadeh, "Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks," in ACM/IEEE International Symposium on Microarchitecture (MICRO), 2020 (Acceptance Rate = 19%).

[C5] S. Ghodrati, H. Sharma, S. Kinzer, A. Yazdanbakhsh , J. Park, N.S. Kim, D. Burger, H. Esmaeilzadeh, ”Mixed-Signal Charge-Domain Acceleration of Deep Neural Networks through Interleaved Bit-Partitioned Arithmetic,” in ACM/IEEE International Conference on Parallel Architectures and Compilation Techniques (PACT), 2020 (Acceptance Rate = 25%).

[C6] S. Ghodrati, H. Sharma, C. Young, N.S. Kim, H. Esmaeilzadeh, "Bit-Parallel Vector Composability for Neural Acceleration," in ACM/IEEE Design Automation Conference (DAC), 2020 (Acceptance Rate = 23%).

[C7] A. Yazdanbakhsh, M. Brzozowski, B. Khaleghi, S. Ghodrati, K. Samadi, N.S. Kim, H. Esmaeilzadeh,”FlexiGAN: An End-to-End Solution for FPGA Acceleration of Generative Adversarial Networks,” in IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM) 2018.