Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Morning Overview on MSN
MIT’s heat-powered silicon chips hit 99% accuracy in math tests
Engineers at MIT have turned one of computing’s biggest headaches, waste heat, into the main act. By sculpting “dust-sized” silicon structures that steer heat as precisely as electrical current, they ...
A new publication from Opto-Electronic Technology; DOI 10.29026/oet.2025.250011 , discusses integrated photonic synapses, neurons, memristors, and ...
A new publication from Opto-Electronic Technology; DOI 10.29026/oet.2025.250011, discusses integrated photonic synapses, neurons, memristors, and neural networks for photonic neuromorphic computing.
Abstract: Sparse matrix multiplication (SpMM) is a critical kernel used in a wide range of applications, but irregular memory access patterns and memory bandwidth bottleneck as well as load imbalance ...
This project simulates the systolic array architecture used in Google's TPU (Tensor Processing Unit). It includes: The staggered injection creates a diagonal wavefront of computation: Cycle 0: A ...
Abstract: Energy efficiency is a persistent issue in FPGA-based matrix processing, especially as embedded systems face increased computing needs. To get around this, we propose a MAC unit design that ...
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Tiny silicon structures compute with heat, achieving 99% accurate matrix multiplication
MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...
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