Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Breadth-First Search (BFS) is widely used in real-world applications including computational biology, social networks, and electronic design automation. The most effective BFS approach has been shown to be a combination of top-down and bottom-up approaches. Such hybrid techniques need to identify a switching point which is conventionally found through expensive trial-and-error and exhaustive search routines.  present an adaptive method based on regression analysis that enables dynamic switching at runtime with little overhead.  improve the performance of our method by exploiting popular heterogeneous platforms and efficiently design the approach for a given architecture. A   155×     155  ×        speedup is achieved over the standard top-down approach on GPUs. Our approach is the first to combine top-down and bottom-up across different architectures. Unlike combination on a single architecture, a mistuned switching point may significantly decrease the performance of cross-architecture combination. Our adaptive method can predict the switching point with high accuracy, leading to   7×     7  ×        speedup compared to the switching point in average case (1000 switching points).
['Yang You', 'Haohuan Fu', 'David A. Bader', 'Guangwen Yang']
I am writing a research paper on a idea Designing and implementing a heuristic cross-architecture combination for graph traversal
[{"from": "human", "value": "I am writing a research paper on a idea Designing and implementing a heuristic cross-architecture combination for graph traversal"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Breadth-First Search (BFS) is widely used in real-world applications including computational biology, social networks, and electronic design automation. The most effective BFS approach has been shown to be a combination of top-down and bottom-up approaches. Such hybrid techniques need to identify a switching point which is conventionally found through expensive trial-and-error and exhaustive search routines.  present an adaptive method based on regression analysis that enables dynamic switching at runtime with little overhead.  improve the performance of our method by exploiting popular heterogeneous platforms and efficiently design the approach for a given architecture. A   155\u00d7     155  \u00d7        speedup is achieved over the standard top-down approach on GPUs. Our approach is the first to combine top-down and bottom-up across different architectures. Unlike combination on a single architecture, a mistuned switching point may significantly decrease the performance of cross-architecture combination. Our adaptive method can predict the switching point with high accuracy, leading to   7\u00d7     7  \u00d7        speedup compared to the switching point in average case (1000 switching points)."}]