Source: Tiger Says Chip Original Author: Tiger Says Chip This article introduces chips specifically designed for AI computation. In the context of the rapid development of artificial intelligence (AI), traditional general-purpose processors (such as CPUs) can no longer meet the growing computational demands. Therefore, AI chips have emerged as the core hardware driving the popularization … Read more
Where Does the “Speed” of FPGAs Come From? Among processor families, FPGAs (Field Programmable Gate Arrays) are renowned for their “hardware-level acceleration,” particularly excelling in fields such as high-performance computing, image processing, and communication protocol processing. Their “speed” does not solely rely on clock frequency (many FPGAs operate at only a few hundred MHz, far … Read more
In the medical field, every technological innovation is crucial to health and hope. Today, we are witnessing a wave of upgrades in medical imaging devices led by FPGAs (Field-Programmable Gate Arrays), which act like a precise surgical knife, opening up a new path for hardware acceleration of image processing algorithms, making medical diagnosis more efficient … Read more
Limitations of GIL (Global Interpreter Lock) The GIL in Python is a mechanism in the CPython interpreter that ensures only one thread executes Python bytecode at a time. This is a bottleneck for CPU-bound pure Python programs, as true parallel execution cannot be achieved even with multiple CPU cores. Advantages of Multiprocessing Using multiprocessing can … Read more
IntroductionIn the field of meteorological data science, the explosive growth of data poses a severe challenge to computational efficiency. Data generated from global climate model outputs, high-resolution satellite remote sensing, and dense observation networks can easily reach TB or even PB levels. Traditional single-process Python scripts often run slowly when handling these CPU-intensive tasks (such … Read more
Thought for a couple of seconds SIMD (Single Instruction, Multiple Data) is a form of parallel computing: a single instruction can operate on multiple data elements simultaneously. Eigen utilizes SIMD instruction sets (such as SSE and AVX on x86, NEON on ARM) to significantly accelerate vector/matrix operations. The main principles and mechanisms include: 1. Data … Read more
In the realm of digital computing, three distinct “core generals” are active. Each has its own role while working in synergy to support all computing needs, from everyday office tasks to AI innovations. These three are the generalist conductor CPU, the parallel powerhouse GPU, and the AI newcomer NPU. Their emergence is not coincidental; rather, … Read more
The secret is that those who follow us are industry leaders and elites. Author: Peng Cheng Source: Semiconductor Industry Overview The NPU (Neural Network Processing Unit, a dedicated chip designed for artificial intelligence computing, has a core advantage in efficiently executing neural network-related operations (such as matrix multiplication, convolution operations, activation function calculations, etc.). Compared … Read more
In the era of artificial intelligence, we often hear terms like CPU, GPU, and NPU. They are all chips that process data, but their design philosophies and areas of expertise are vastly different. Understanding their differences is akin to understanding the different roles in an efficient team: the commander, the strongman, and the expert. 1. … Read more
Click on the above Industry 4.0 to follow us e-works encourages originality, please refer to the homepage for submission guidelines on “Original Contributions“. ✎ Introduction Recently, there has been significant movement in the U.S. stock market. Two tech stock concepts have suddenly gained popularity, attracting high market attention with astonishing price increases. These two concepts … Read more