Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The continued evolution of modern hardware has brought several new challenges to database management#R##N##R##N#systems (DBMSs). Multicore CPUs are now mainstream, while the future lies in massively parallel computing#R##N##R##N#performed on many-core processors. Hover, because they re developed originally for single-core#R##N##R##N#processors, DBMSs cannot take full advantage of the parallel computing that uses so many cores. Several#R##N##R##N#components in the traditional database engines become new bottlenecks on multicore platforms. ,#R##N##R##N# analyze the bottlenecks in existing database engines on a modern multicore platform using the mixed#R##N##R##N#workload of the TPC-W benchmark and describe strategies for higher scalability and throughput for existing#R##N##R##N#DBMSs on multicore platforms. First,  show how to overcome the limitations of the database engine#R##N##R##N#by introducing a partition-based multi-instance database system on a single multicore platform without any#R##N##R##N#modification of existing DBMSs. Second,  analyze the possibility of further improving the performance#R##N##R##N#by optimizing the cache performance of concurrent queries. Implemented by middleware, our proposed PM-DB#R##N##R##N#can avoid the challenging work of modifying existing database engines. Performance evaluation using#R##N##R##N#the TPC-W benchmark revealed that our proposal can achieve at most 2.5 times higher throughput than the#R##N##R##N#existing engine of PostgreSQL.
['Fang Xi', 'Takeshi Mishima', 'Haruo Yokota']
I am writing a research paper on a idea PM-DB: Partition-based Multi-instance Database System for Multicore Platforms
[{"from": "human", "value": "I am writing a research paper on a idea PM-DB: Partition-based Multi-instance Database System for Multicore Platforms"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The continued evolution of modern hardware has brought several new challenges to database management#R##N##R##N#systems (DBMSs). Multicore CPUs are now mainstream, while the future lies in massively parallel computing#R##N##R##N#performed on many-core processors. Hover, because they re developed originally for single-core#R##N##R##N#processors, DBMSs cannot take full advantage of the parallel computing that uses so many cores. Several#R##N##R##N#components in the traditional database engines become new bottlenecks on multicore platforms. ,#R##N##R##N# analyze the bottlenecks in existing database engines on a modern multicore platform using the mixed#R##N##R##N#workload of the TPC-W benchmark and describe strategies for higher scalability and throughput for existing#R##N##R##N#DBMSs on multicore platforms. First,  show how to overcome the limitations of the database engine#R##N##R##N#by introducing a partition-based multi-instance database system on a single multicore platform without any#R##N##R##N#modification of existing DBMSs. Second,  analyze the possibility of further improving the performance#R##N##R##N#by optimizing the cache performance of concurrent queries. Implemented by middleware, our proposed PM-DB#R##N##R##N#can avoid the challenging work of modifying existing database engines. Performance evaluation using#R##N##R##N#the TPC-W benchmark revealed that our proposal can achieve at most 2.5 times higher throughput than the#R##N##R##N#existing engine of PostgreSQL."}]