As we all know, high computing power has become a key requirement in many fields, and a new era of computing has quietly opened as global enterprises shift from general-purpose computing to accelerated computing and generative AI.
Source: Chiple.
Whether it's artificial intelligence, big data analytics, cloud computing, or the Internet of Things, powerful computing power is required to process massive amounts of data and complex algorithmsIn this context, chip manufacturers are pursuing higher computing power to meet the needs of the market.
In particular, as increasing computing power is not just a simple technical upgrade, the cost of hardware design is also rising dramatically.
To achieve this, chipmakers need to adopt more advanced process technologies and more complex design approaches;This not only requires a lot of R&D investment, but also many technical difficulties to be solved in the production process.
In addition, the demand for computing power and data for large models has shown a first-class growth, which will also bring a new proposition to chip companies.
The EBL electron beam lithography machine can achieve 07nm chip fabrication.
First of all, the advanced process technology has already entered the nano scale from the micron level;Today, the concept of the picometer level has also emerged.
A smaller process technology can increase the number of transistors integrated on the chip, thereby increasing the computing power of the chipFor example, some advanced chip design technologies: heterogeneous integration, multi-core processors, parallel computing, etc. ）
Secondly, strategy is also an important aspect of the pursuit of high computing power: chip manufacturers need to formulate reasonable product strategies and market strategies to meet the needs of different fields.
For high-performance computing needs in AI and cloud computing, chipmakers can design application-specific integrated circuits (ASICs) or field-programmable gate arrays (FPGAs) to deliver higher computing power and efficiency.
Of course, in response to the needs of the Internet of Things, it is necessary to design low-power, low-cost chips to meet the requirements of large-scale deployment.
Chiplet enables the next generation of chip design ecology.
Due to the rapid development of large-scale model AI, the contradiction between computing power and data supply and demand has become more prominent, and the deployment of computing power on the data side has become the core key to reducing costs and increasing efficiency of large models from computing-intensive scenarios to data-heavy scenarios.
However, there is a premise for the decoupling of software and hardware: in the actual work of chips and systems, the energy consumption of computing accounts for only a small part of the entire process, and reducing data handling is the key to improving efficiency.
Labor costs:Add a large number of professional talents, including designers, engineers, testers, etc.;These personnel need to have deep expertise, skills and experience, so the labor cost is high.
Technical Cost:Adopt state-of-the-art technologies and tools such as EDA (Electronic Design Automation) tools, physical verification tools, etcThese tools need to be continuously updated and upgraded to meet technical challenges and design needs.
R&D Costs:The R&D cycle of chip hardware design is long, and it needs to go through many iterations and optimizationsDuring the R&D process, various experiments and tests are carried out to ensure the feasibility and performance of the design.
Cost of Intellectual Property:Chip hardware design involves a large number of intellectual property issues, such as patents, trademarks, etc.;In order to protect the corresponding intellectual property rights, a large number of applications, maintenance and management are required.
In short, although this change is still neededTime has passed, but the trend is clear.
With the advent of the era of large models, the rapid growth of computing power and data demand has brought unprecedented challenges and opportunities to the chip industryAs chiplet technology chipmaker, Chipuller is well-positioned to take on this change.
Chipuller has been committed to technological innovation and product research and development, and through continuous investment in research and development, Chipuller has mastered a number of core technologies, including advanced process technology, a single chip with efficient customized function combination, and intelligent algorithm optimization.
In addition, Chipuller is actively exploring new business models and business areasIn the chip industry, the business model and market demand are constantly changing, and Qipule keeps up with the market trend and constantly expands its product lines and application fields to meet the changing market demand.
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Finally, in the end, through a quote from Wang Yangming:
Whoever is not diligent in learning will not be diligent.
May every semiconductor practitioner be able to——
The height of the up, the strength of the drill!