| Budget Amount *help |
¥16,510,000 (Direct Cost: ¥12,700,000、Indirect Cost: ¥3,810,000)
Fiscal Year 2020: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2019: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2018: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2017: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2016: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
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| Outline of Final Research Achievements |
Most research in algorithms since the 1970s has been for single processor machines, resulting in a vast amount of sophisticated and robust software. Unfortunately most of this software profits very little when run on the now prevalent multiprocessor hardware. The redesign and re-implementation for all of this software will be an extremely time consuming and expensive task. The purpose of this research is to efficiently parallelize algorithms without any essential change to their existing implementation. This is achieved by adding parallelization as a wrapper to the existing code. This technique will be applied in particular to certain tree search algorithms used in optimization, artificial intelligence and machine learning. International research collaboration is a major part of our project.
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