High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...

This is the second in a series of discussions with Mike Glass, owner of Orion Technical Solutions, on ensuring data integrity ...

Abstract: In this paper, we propose three modular multiplication algorithms that use only the IEEE 754 binary floating-point operations. Several previous studies have used floating-point operations to ...

When you create an algorithm, you need to include precise, step-by-step instructions. This means you will need to break down the task or problem into smaller steps. We call this process decomposition.

A simple, low cost, and precision frequency meter uses only two pins of a pc parallel port (Figure 1). The TTL-level periodic input signal with frequency f IN connects to the ACK pin of LPT1. This ...

As Transformer models continue to grow in size and complexity, numerous high-fidelity pruning methods have been proposed to mitigate the increasing parameter count. However, transforming these ...

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 ...