Numerical computation and mathematical software form the backbone of modern scientific inquiry, facilitating the approximation of real numbers, the solution of complex mathematical models, and the ...
Abstract: Graph convolutional networks (GCNs) are emerging neural network models designed to process graph-structured data. Due to massively parallel computations using irregular data structures by ...
Abstract: In this paper, we propose three modular multiplication algorithms that use only the IEEE 754 binary floating-point operations. Several previous studies have used floating-point operations to ...
This repository contains the experimental code and raw results used in the study: "Time, Space and Energy Complexity Analysis of Sorting and Matrix Multiplication Algorithms" The project evaluates ...
This project implements an 8x8 systolic array for high-performance matrix multiplication, leveraging a parallel processing architecture optimized for efficiency and scalability. The workflow spans RTL ...
Siddhesh Surve is an accomplished Engineering leader with topics of interest including AI, ML, DS, DE, Cloud compute.
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