Chip cost
Algorithm deployment cost
Cloud expenditure cost
As an innovative chip architecture, processing-in-memory integrates data storage and computation by embedding computing capabilities within memory, significantly enhancing computational efficiency and energy efficiency ratios. It is suitable for fields such as high-performance computing and big data analysis and excels in complex algorithms such as artificial intelligence, large models, and machine learning. Additionally, processing-in-memory technology reduces data transmission latency and energy consumption, improving system reliability and security. For meeting the needs of companies and government agencies, industry solutions based on processing-in-memory can provide efficient, secure, and reliable computing services, facilitating digital transformation and intelligent upgrades.
Chip cost
Algorithm deployment cost
Cloud expenditure cost
Disruptive high energy efficiency
Realize ultra-low energy consumption cost
Simplify customer deployment interfaces
System application costs decreases
Structured raw data
communication bandwidth requirements decreases
Multimodal data feature extraction
Multi-scenario adaptation