| Budget Amount *help |
¥17,160,000 (Direct Cost: ¥13,200,000、Indirect Cost: ¥3,960,000)
Fiscal Year 2022: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2021: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2020: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2019: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2018: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
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| Outline of Final Research Achievements |
Towards highly-productive GPGPU programming languages, this project obtained the following results. It proposed a novel algorithm for dynamic memory management allocation, which is one of the primary obstacles that prevents from using object-oriented programming on GPU. The algorithm was implemented as a domain-specific language for C++, called DynaSOAr, which allocates memory as fast as existing memory allocaters, yet allocates more densely, resulting in faster overall application execution. Based on this work, the project further studied on advanced object-oriented language features including inheritance, modularity, and dynamic compilation.
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