Abstract: Matrix multiplication is a fundamental computational operation widely used in various engineering applications. To accelerate large-scale matrix multiplication, computing tasks are commonly ...
A team of researchers developed “parallel optical matrix-matrix multiplication” (POMMM), which could revolutionize tensor ...
AMD is preparing a significant redesign of its CPU architecture with the upcoming Zen 6 generation, signaling a clear break ...
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 ...
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 ...
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 ...
Quantum-inspired adaptive tiling for high-performance matrix multiplication. Uses WKB tunneling physics with the golden ratio to derive optimal tile sizes from real-time CPU state. 15%+ gains on ...
Abstract: We present Modular Polynomial (MP) Codes for Secure Distributed Matrix Multiplication (SDMM). The construction is based on the observation that one can decode certain proper subsets of the ...