Kyushu University Academic Staff Educational and Research Activities Database
List of Presentations
Kazuki Yoshizoe Last modified date:2023.05.29

Professor / Section of Advanced Computational Science / Research Institute for Information Technology


Presentations
1. Scalable Parallelization of a Numerical Constraint Solver.
2. Implementing Parallel Speculative Execution of Loops on JVM
There have been several proposals about hardware speculative executions, in a larger gran-ularity than instruction level parallelism, by partitioning the target program into blocks.We have applied speculative execution onto Java Virtual Machine. We implemented it on a shared memory machine. The target for speculative execution is limited to loops. We measured speedups for simple loops and found that it is possible to gain speedups for loops which contains more than 10000 instructions by an interpreter Java Virtual Machine..
3. 美添一樹, 今井浩, 囲碁の部分問題における両利きの探索, 情報処理学会研究報告. GI, [ゲーム情報学], 2005.09, 囲碁においては、盤面全体に対する、速く正確な評価関数を作ることは困難である。そのため、小目標ごとのサーチが、囲碁プログラムの間では広く用いられている。ここで問題になるのが小目標間の依存関係である。小目標の勝敗に影響を与える範囲を求めて依存関係を解決するアプローチが研究され始めている。relevancy zoneという概念が使われ始めているが、この求め方を改良することを目標としたアルゴリズムを提案する。二つの小目標についてそのような範囲が重なっていれば、そこが両利きの候補となる。.
4. Df-pn Algorithm with Dynamic Widening.
5. Depth-First UCT and Its Application to Go.
6. Acceleration of Monte-Carlo Go by FPGA-based Hardware
In the monte-carlo simulation of Go, it takes time to run playouts. There were attempts of accelerating by implementing circuits for playout on FPGA, but it is difficult to realize high-speed playouts because of high utilization of resources in a FPGA. In this paper, we propose an algorithm, Triple Line-based Playout for Go (TLPG) to accelerate playouts for the monte-carlo tree search for computer-go game. We implemented the playout logics on FPGA for 9x9 and 19x19 boards. With the optimizations, We achieved 13104playouts/sec in 9x9 and 2055playouts/sec in 19x19 board in simulation. By making games with GNU Go on a host Computer, We evaluation the playouts of TLPG..
7. A Proposal for Distributed Parallel Monte Carlo Tree Search Framework
We propose to implement a framework for Monte Carlo Tree Search (MCTS) on distributed parallel systems. The objective is to facilitate the parallelization of existing sequential Monte Carlo Tree Search programs. It is expected to be effective for highly parallel distributed systems by using Transposition table Driven Scheduling as the parallelization technique for the framework..
8. Using local minima to accelerate Krawczyk-Hansen global optimization.
9. Df-pn Algorithm with Dynamic Widening.
10. Depth-First UCT and Its Application to Go.
11. Junichi Hashimoto, Akihiro Kishimoto, Kazuki Yoshizoe, Kokolo Ikeda, Accelerated UCT and Its Application to Two-Player Games, Advances in Computer Games 13, 2011.11.
12. Implementing Parallel Speculative Execution of Loops on JVM
There have been several proposals about hardware speculative executions, in a larger gran-ularity than instruction level parallelism, by partitioning the target program into blocks.We have applied speculative execution onto Java Virtual Machine. We implemented it on a shared memory machine. The target for speculative execution is limited to loops. We measured speedups for simple loops and found that it is possible to gain speedups for loops which contains more than 10000 instructions by an interpreter Java Virtual Machine..
13. 美添一樹, 今井浩, 囲碁の部分問題における両利きの探索(Session 3), 情報処理学会研究報告. GI, [ゲーム情報学], 2005.09, 囲碁においては、盤面全体に対する、速く正確な評価関数を作ることは困難である。そのため、小目標ごとのサーチが、囲碁プログラムの間では広く用いられている。ここで問題になるのが小目標間の依存関係である。小目標の勝敗に影響を与える範囲を求めて依存関係を解決するアプローチが研究され始めている。relevancy zoneという概念が使われ始めているが、この求め方を改良することを目標としたアルゴリズムを提案する。二つの小目標についてそのような範囲が重なっていれば、そこが両利きの候補となる。.
14. Acceleration of Monte-Carlo Go by FPGA-based Hardware
In the monte-carlo simulation of Go, it takes time to run playouts. There were attempts of accelerating by implementing circuits for playout on FPGA, but it is difficult to realize high-speed playouts because of high utilization of resources in a FPGA. In this paper, we propose an algorithm, Triple Line-based Playout for Go (TLPG) to accelerate playouts for the monte-carlo tree search for computer-go game. We implemented the playout logics on FPGA for 9x9 and 19x19 boards. With the optimizations, We achieved 13104playouts/sec in 9x9 and 2055playouts/sec in 19x19 board in simulation. By making games with GNU Go on a host Computer, We evaluation the playouts of TLPG..
15. A Proposal for Distributed Parallel Monte Carlo Tree Search Framework
We propose to implement a framework for Monte Carlo Tree Search (MCTS) on distributed parallel systems. The objective is to facilitate the parallelization of existing sequential Monte Carlo Tree Search programs. It is expected to be effective for highly parallel distributed systems by using Transposition table Driven Scheduling as the parallelization technique for the framework..
16. Scalable Parallelization of a Numerical Constraint Solver.
17. Optimization of Playout Policy Integrated with Monte-Carlo Tree Search.
18. Using local minima to accelerate Krawczyk-Hansen global optimization.
19. An Extended GLB Library for Optimization Problems.