A Framework for Machine Learning Algorithms on the Cloud

Research Project

Project/Area Number	22700048
Research Category	Grant-in-Aid for Young Scientists (B)
Allocation Type	Single-year Grants
Research Field	Computer system/Network
Research Institution	Waseda University
Principal Investigator	AKIOKA Sayaka 早稲田大学, IT研究機構, 准教授 (90333533)
Project Period (FY)	2010 – 2011
Project Status	Completed (Fiscal Year 2011)
Budget Amount *help	¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000) Fiscal Year 2011: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000) Fiscal Year 2010: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
Keywords	機械学習 / 並列分散処理 / クラウドコンピューティング / 学習アルゴリズム / Frequent Pattern Mining / 並列分散コンピューティング / GPGPU
Research Abstract	This proposal originally tried to develop a framework, which enables to run machine learning algorithms in parallel on the computational cloud with the full input from the very fast and huge data source such as Twitter. However, several experiments in this project have revealed that a couple dozen CPUs in the cloud are enough to process all the inputs in a pipeline. For the higher level of the parallelism, such as the execution on GPGPUs, the drastic speed-up of the input is unavoidable.