My research interests lie in theoretical computer science. My work thus far has focused on theoretical cryptography, particularly lattice-based cryptography. I am interested in studying the foundations of quantum computing, complexity theory, and cryptography, along with formal logic, and exploring their interconnections.
In the past, I have worked on projects related to discrete mathematics and computer architecture and systems.
Modern language models like BERT have revolutionized natural language processing tasks but are computationally intensive, limiting their deployment on edge devices. This paper presents an energy-efficient accelerator design tailored for encoder-based language models, enabling their integration into mobile and edge computing environments. A dataflow-aware hardware accelerator design for language models inspired by SIMBA, use of Approximate Fixed-Point POSIT (AFPOS) based multipliers, and use of high bandwidth memory achieves significant improvements in computational efficiency, power consumption, area, and latency compared to the hardware-realized scalable accelerator Simba. Compared to SIMBA, AxLaM achieves 9x energy reduction, 58% area reduction and 1.2x improved latency, making it suitable for deployment in edge devices. The energy efficiency of AxLaN is 1.8 TOPS/W, 65% higher than FACT which needs pre-processing of language model before implementing it on the hardware.
On the Existence of Balanced Generalized de Bruijn Sequences
Bhumika Mittal, Haran Mouli, Eric Tang, and 1 more author
A balanced generalized de Bruijn sequence with parameters (n,l,k) is a cyclic sequence of n bits such that (a) the number of 0’s equals the number of 1’s, and (b) each substring of length l occurs at most k times. We determine necessary and sufficient conditions on n,l, and k for the existence of such a sequence.
Ring Trapdoor Functions: A Lattice-Based Framework for Secure Ring Signatures
Modern language models like BERT have revolutionized natural language processing tasks but are computationally intensive, limiting their deployment on edge devices. This paper presents an energy-efficient accelerator design tailored for encoder-based language models, enabling their integration into mobile and edge computing environments. A dataflow-aware hardware accelerator design for language models inspired by SIMBA, use of Approximate Fixed-Point POSIT (AFPOS) based multipliers, and use of high bandwidth memory achieves significant improvements in computational efficiency, power consumption, area, and latency compared to the hardware-realized scalable accelerator Simba. Compared to SIMBA, AxLaM achieves 9x energy reduction, 58% area reduction and 1.2x improved latency, making it suitable for deployment in edge devices. The energy efficiency of AxLaN is 1.8 TOPS/W, 65% higher than FACT which needs pre-processing of language model before implementing it on the hardware.
On the Existence of Balanced Generalized de Bruijn Sequences
Bhumika Mittal, Haran Mouli, Eric Tang, and 1 more author
A balanced generalized de Bruijn sequence with parameters (n,l,k) is a cyclic sequence of n bits such that (a) the number of 0’s equals the number of 1’s, and (b) each substring of length l occurs at most k times. We determine necessary and sufficient conditions on n,l, and k for the existence of such a sequence.
Ring Trapdoor Functions: A Lattice-Based Framework for Secure Ring Signatures