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Scientists build first in-memory sorting chip without comparators
A new computing era arrives with the breakthrough in how computers can sort information. This vital function, at the heart of ...
Two former Google DeepMind researchers who worked on the company’s Nobel Prize-winning AlphaFold protein structure prediction AI as well as its AlphaEvolve code generation system have launched a new ...
This project demonstrates the use of the MapReduce framework to solve the matrix multiplication problem. Matrix multiplication is a common computational task in fields like scientific computing, ...
Abstract: Multi-scalar multiplication (MSM) is the primary computational bottleneck in zero-knowledge proof protocols. To address this, we introduce FAMA, an FPGA-oriented MSM accelerator developed ...
Abstract: The Multiply and Accumulator (MAC) in Convolution Neural Network (CNN) for image applications demands an efficient matrix multiplier. This study presents an area- and power-efficient ...
The goal of this assignment is to implement high-performance CUDA kernels for tensor operations and integrate them with the MiniTorch framework. You will implement low-level operators in CUDA C++ and ...
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