IEEE

Multiplication-Free Lookup-Based CNN Accelerator Using Residual Vector Quantization and Its FPGA Implementation

Abstract: In this paper, a table lookup-based computing technique is proposed to perform convolutional neural network (CNN) inference without multiplication, and its FPGA implementation is ...
IEEE

Area-Efficient Matrix-Vector Polynomial Multiplication Architecture for ML-KEM Using Interleaving and Folding Transformation

Abstract: The ML-KEM post-quantum cryptography (PQC) scheme requires matrix-vector polynomial multiplication and polynomial arithmetic operations in the number theoretic transform (NTT) domain. Prior ...
GitHub

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

CUDA-L2 is a system that combines large language models (LLMs) and reinforcement learning (RL) to automatically optimize Half-precision General Matrix Multiply (HGEMM) CUDA kernels. CUDA-L2 ...