5 papers
TsetlinWiSARD: On-Chip Training of Weightless Neural Networks using Tsetlin Automata on FPGAs
Shengyu Duan, Marcos L. L. Sartori, Rishad Shafik +1
Increasing demands for adaptability, privacy, and security at the edge have persistently pushed the frontiers for a new generation of machine learning (ML) algorithms with training…
Fast and Compact Tsetlin Machine Inference on CPUs Using Instruction-Level Optimization
Yefan Zeng, Shengyu Duan, Rishad Shafik +1
The Tsetlin Machine (TM) offers high-speed inference on resource-constrained devices such as CPUs. Its logic-driven operations naturally lend themselves to parallel execution on mo…
A Tsetlin Machine Image Classification Accelerator on a Flexible Substrate
Yushu Qin, Marcos L. L. Sartori, Shengyu Duan +3
This paper introduces the first implementation of digital Tsetlin Machines (TMs) on flexible integrated circuit (FlexIC) using Pragmatic's 600nm IGZO-based FlexIC technology. TMs,…
Dynamic Tsetlin Machine Accelerators for On-Chip Training at the Edge using FPGAs
Gang Mao, Tousif Rahman, Sidharth Maheshwari +4
The increased demand for data privacy and security in machine learning (ML) applications has put impetus on effective edge training on Internet-of-Things (IoT) nodes. Edge training…
IMPACT:InMemory ComPuting Architecture Based on Y-FlAsh Technology for Coalesced Tsetlin Machine Inference
Omar Ghazal, Wei Wang, Shahar Kvatinsky +3
The increasing demand for processing large volumes of data for machine learning models has pushed data bandwidth requirements beyond the capability of traditional von Neumann archi…