AI chipsets for data center: Markets, technology, products and market forecast

The race for making perfect hardware to accelerate artificial intelligence (AI) applications has begun and many companies are jumping in with their products and solutions. AI acceleration has become a buzzword of the market and many companies have introduces their chipset products. Compute has made significant progress in the last couple of years with many chipsets coming to market. This report focuses on the AI acceleration chipsets for enterprise and data center market from a market and technology point of view.

The reports analyzes technology and business trends for the AI acceleration chipset products: CPU, GPU, FPGA and ASIC. There are four parts to the report, markets, technology, products and forecast.

The market part focuses on use cases, applications and vertical markets. A summary of different data types, AI usage and infrastructure purchase is provided. The report also looks at hyperscalers and cloud as a market and analyzes differences between the buyers such as hyperscalers and enterprises. A preview of the market drivers, challenges and business models is also provided.

The technology part focuses on wide range of aspects such as acceleration needs, architecture, bus interface, AI application needs, scaling, alternate architectures and utilization. It also identifies how different chipset architectures such as CPU, GPU, FPGA and ASIC provide AI acceleration.

The product section focuses on different vendors, their products, differentiators and our assessment. Products for both training and inference acceleration are considered along with pricing and business model aspect. A list of buyers and users is provided for each vendor based on publicly available information. We have also evaluated various start-ups and how they could pose threat to dominant players. Finally, profile of key companies along with comprehensive listing of vendors is provided.

Market forecast part provides complete forecast for data center chipsets till 2026. The forecast includes hardware unit shipments, average selling prices, and revenue. The report also includes profiles of key industry players and analyst comments.

Key Questions Addressed

• What are key driving factors for AI acceleration
• What are challenges for AI chipset companies?
• How has the AI hardware market evolved in the past couple of years?
• What are some of the new technologies being used in compute acceleration?
• What are the key Ai applications within enterprises using chipsets?
• What are prominent use cases and applications for AI in the enterprise market?
• What are the acceleration needs of different use cases?
• What are some of the popular data types that need AI acceleration?
• Who are the key players in the AI chipset market, and what are their relative strengths and weaknesses?
• What is the size of the market opportunity in different chipset categories, and why will some grow faster than others over the next 5 years?