TAILIEUCHUNG - Báo cáo khoa học: "An Efficient Parallel Substrate for Typed Feature Structures on Shared Memory Parallel Machines"

This paper describes an efficient parallel system for processing Typed Feature Structures (TFSs) on shared-memory parallel machines. We call the system Parallel Substrate for TFS (PSTFS}. PSTFS is designed for parallel computing environments where a large number of agents are working and communicating with each other. Such agents use PSTFS as their low-level module for solving constraints on TFSs and sending/receiving TFSs to/from other agents in an efficient manner. | An Efficient Parallel Substrate for Typed Feature Structures on Shared Memory Parallel Machines NINOMIYA Takashit TORISAWA Kentaro1 and TSUJII Jun ichitt Department of Information Science Graduate School of Science University of Tokyo CCL UMIST . Abstract This paper describes an efficient parallel system for processing Typed Feature Structures TFSs on shared-memory parallel machines. We call the system Parallel Substrate for TFS PSTFS . PSTFS is designed for parallel computing environments where a large number of agents are working and communicating with each other. Such agents use PSTFS as their low-level module for solving constraints on TFSs and send-ing receiving TFSs to from other agents in an efficient manner. From a programmers point of view PSTFS provides a simple and unified mechanism for building high-level parallel NLP systems. The performance and the flexibility of our PSTFS are shown through the experiments on two different types of parallel HPSG parsers. The speed-up was more than 10 times on both parsers. 1 Introduction The need for real-time NLP systems has been discussed for the last decade. The difficulty in implementing such a system is that people can not use sophisticated but computationally expensive methodologies. However if we could provide an efficient tool environment for developing parallel NLP systems programmers would have to be less concerned about the issues related to efficiency of the system. This became possible due to recent developments of parallel machines with shared-memory architecture. We propose an efficient programming environment for developing parallel NLP systems on shared-memory parallel machines called the Parallel Substrate for Typed Feature Structures PSTFS . The environment is based on agent-based object-oriented architecture. In other words a system based on PSTFS has many computational agents running on different processors in parallel those agents communicate with each other by using messages including TFSs. .

• Báo cáo khoa học
• An Efficient Parallel Substrate for Typed Feature Structures
• Shared Memory
• Parallel Machines
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
• Ngôn ngữ tự nhiên
• Kỹ thuật lập trình
• Xử lý nhập nhằng ngữ nghĩa
• Xử lý ngữ nghĩa
• Xử lý ngôn ngữ
• Natural Language Processing
• Ngôn ngữ lập trình
• Nhập nhằng cấu trúc
• Tri thức về ngôn ngữ
• Mô hình n gram
• Dịch máy
• Phương pháp dịch máy
• Hiểu ngôn ngữ
• Phân tích ngữ nghĩa
• Phân loại tin tự động
• Biểu diễn vị từ
• Thuộc tính về sự kiện
• Thuộc tính về sự kiện
• Mô hình ngôn ngữ Google Book N grams
• Mô hình ngôn ngữ KenLM
• Phương pháp làm mịn
• Tách từ tiếng Việt
• Gán nhãn từ loại
• Phân tích cú pháp
• Nghĩa từ vựng
• Phân giải nhập nhằng từ
• Phân loại văn bản
• Lexical chain
• Phản hồi thông tin
• Bài toán PTCP
• Cấu trúc ngữ pháp
• Phân tích cú pháp xác suất
• CKY kết hợp xác suất
• Văn phạm phi ngữ cảnh xác suất
• Hình thái học