Graph analytics is critical in domains such as social network analysis, logistics, and cybersecurity. NetworkX is one of the most popular Python libraries in this space, widely appreciated for its ease of use and comprehensive collection of algorithms. However, as graph datasets increase in size and complexity, NetworkX’s CPU-based computations become a significant bottleneck, leading to slow processing times.