Communications of the ACM

The Innovation Engine: Government-Funded Academic Research

Reduced Instruction Set Computer (RISC).25 Simplified instruction sets enabled faster microprocessors. Today, 99% of all ...

Cai Cai's Machine Learning Sklearn Class: Understandable from Scratch, from Model Invocation to Practical Implementation

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to ...
IEEE

TGBNN: Training Algorithm of Binarized Neural Network With Ternary Gradients for MRAM-Based Computing-in-Memory Architecture

Abstract: To build Neural Networks (NNs) on edge devices, Binarized Neural Network (BNN) has been proposed on the software side, while Computing-in-Memory (CiM) architecture has been proposed on the ...
GitHub

Wang-Xiaodong1899/ms-swift-RL

šŸ² ms-swift is an official framework provided by the ModelScope community for fine-tuning and deploying large language models and multi-modal large models. It currently supports the training ...
GitHub

High-performance Python rate limiting library with multiple algorithms (Fixed Window, Sliding Window, Token Bucket, Leaky Bucket & GCRA) and storage backends (Redis, In ...

in-memory Use In-Memory as storage backend. redis Use Redis as storage backend. If you want to throttle the same Key at different locations in your program, make sure that Throttled receives the same ...
IEEE

IDWA: A Importance-Driven Weight Allocation Algorithm for Low Writeā€“Verify Ratio RRAM-Based In-Memory Computing

Abstract: Resistive random access memory (RRAM)-based in-memory computing (IMC) architectures are currently receiving widespread attention. Since this computing approach relies on the analog ...