Graph Program Acceleration System for Hardware-Independent Analysis

The patent introduces an intermediary layer (graph analysis system) that sits between the high-level algorithm description and the hardware-specific execution. This system automatically performs platform-specific optimizations, transformations, and code generation, allowing algorithms to achieve hardware-optimized performance without requiring developers to directly handle hardware complexity. The intermediary handles tasks such as partitioning graph data, selecting appropriate algorithms, and generating optimized code for different platforms.

The system performs preliminary actions by automatically analyzing the high-level graph analysis program, generating optimized intermediate representations, and preparing platform-specific code before execution. This includes pre-processing steps such as graph partitioning, algorithm selection, and code transformation that convert high-level descriptions into efficient low-level code, thereby maintaining ease of programming while achieving high execution efficiency.

The patent applies segmentation by dividing large graph data sets into smaller partitions or chunks that can be processed independently or in parallel. This allows the system to handle large-scale graphs by breaking them down into manageable pieces, processing each partition with appropriate algorithms, and combining results. This segmentation approach enables scalability to large data sets while controlling memory usage by processing data in smaller units rather than loading entire graphs into memory.