R. S. Raju, K. Daruwalla, M. Lipasti, Accelerating Deep Learning with Dynamic Data Pruning, preprint under review, November, 2021. https://arxiv.org/abs/2111.12621.
[pdf]
K. Daruwalla, M. Lipasti, Information Bottleneck-Based Hebbian Learning Rule Naturally Ties Working Memory and Synaptic Updates, preprint, September, 2021. https://arxiv.org/abs/2111.13187.
[pdf]
K. Daruwalla, H. Zhuo, C. Schulz, M. Lipasti, BitBench: A Benchmark for Bitstream Computing, Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES '19), June 23, 2019. http://dl.acm.org/citation.cfm?doid=3316482.3326355.
[pdf]
K. Daruwalla, H. Zhuo, R. Shukla, M. Lipasti, BitSAD v2: Compiler Optimization and Analysis for Bitstream Computing, ACM Transcations on Architecture and Code Optimization (TACO), Vol. 16, Iss. 4, No. 43. November 2019. https://dl.acm.org/citation.cfm?id=3364999.
[pdf]
K. Daruwalla, N. Olivero, A. Pluger, S. Rao, D.W. Chang, M. Simoni, A quantitative analysis of the performance of computing architectures used in neural simulations, Journal of Neuroscience Methods, Vol. 311. 2019, Pg. 57-66. http://www.sciencedirect.com/science/article/pii/S0165027018303017.
[link]
K. Daruwalla, H. Zhuo, M. Lipasti, BitSAD: A Domain-Specific Language for Bitstream Computing, First ISCA Workshop on Unary Computing, June 2019.
[pdf] [slides]
K. Daruwalla, M. Lipasti, Resource Efficient Navigation Using Bitstream Computing, First ISCA Workshop on Unary Computing, June 2019.
[pdf]
Building Energy-Efficient Computers,
Invited talk: Cold Spring Harbor Lab NeuroAI Seminar, Long Island, NY. Feb. 2022.
[slides]
BitSAD v2: Compiler Optimization and Analysis for Bitstream Computing,
High-performance Embedded Architecture and Compilation Conference, Bologna, Italy. Jan. 2020.
[slides]
Resource Efficient Navigation Using Bitstream Computing,
First ISCA Workshop on Unary Computing, Phoenix, AZ. Jun. 2019.
[slides]
BitBench: A Benchmark for Bitstream Computing,
Languages, Compilers, and Tools for Embedded Systems, Phoenix, AZ. Jun. 2019.
[slides]
Seeing Through the FoG: A Biologically Inspired Navigation System,
Industry Affiliates Meeting, Madison, WI. Oct. 2017.
A Biologically-Plausible Learning Rule Based on the Information Bottleneck,
Spiking Neural networks as Universal Function Approximators (SNUFA '21), Nov. 2021.
[poster]
BitBench: A Benchmark for Bitstream Computing,
Languages, Compilers, and Tools for Embedded Systems (LCTES '19), Phoenix, AZ. Jun. 2019.
Seeing Through the FoG: A Biologically Inspired Navigation System,
Industry Affiliates Meeting, Madison, WI. Oct. 2017.
Drone Control with Map-Seeking Circuits,
Industry Affiliates Meeting, Madison WI. Nov. 2016.