This note contains a short informal description of how OPTi draws the limit set, together with an introduction to programming for mathematicians.

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As computing technologies have been developed rapidly and continuously, statistical languages should be frequently improved by adopting them for realizing comfortable statistical environments. Although that work was a difficult task before, we can implement such languages easily by modern software techniques such as the Java language, which unifies recent computer technologies widely and neatly.
In this paper, we describe the idea of a new Jasp (JAva based Statistical Processor) language, which is a function-based and object-oriented language, is suitable for interactive operation, and has flexibilities and diverse extensibilities. Considering required characteristics for a statistical language, we decide to implement the Jasp language by Java technologies through the Pnuts language, which is a script language written in Java, and a preprocessing approach. This implementation brings several advantages such as reduction of development costs, effective uses of existing resources, and adequate reliabilities.

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A statistical system needs to be able to work with other systems in a flexible way and be easily extensible, because no one statistical system can implement all the features required by a wide variety of users. Recently, new ways of extending statistical systems have been brought about by the rapid development of software technologies, including the Java language. In this paper, we propose the use of several Java language techniques for realizing extensions of Jasp, a Java-based statistical system, and demonstrate three practical features of these extensions.
The first practical feature is demonstrated in the ability to handle eXtensible Markup Language (XML) documents, which are the standard format for data transmission on the WWW. The second practical feature is the use of the Component Object Model (COM) interface of Microsoft Windows for communication, e.g., with Microsoft Excel. The third practical feature is the sharing of program resources from other statistical software products, and to perform this task we have extended Jasp by using a translator to execute functions written in the XploRe language.

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イメージ符号型文書ファイルのリモート目視検索について報告する.ファイルサーバからLAN経由でリモートワークステーションへイメージ符号文書データを転送する手法について述べており, その圧縮イメージ符号文書の新しい取扱い方法を提案した.また, ネットワーク経由での文書転送速度を考察し, 高速ページ転送を検証した.実験システムは, 文書の圧縮符号化ボードとアプリケーションプログラム以外は既存汎用装置で構成した.文書ファイルサーバは, 書換型光ディスクを備えたワークステーションで構成し, LANにはEthernetとTCP/IPを使用した.文書のLAN転送は, MH符号と間引き画像データの使い分けで実験した.結果として, 改頁指示操作から表示開始までの応答速度として, 4本/mm相当のCRT表示のとき約4秒/ページ, 2本/mmのとき約2秒/ページの改ページ速度が得られることを確認した.これらの結果は, LANを利用するOAの推進に貢献する.

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In this paper, we describe the details of the design and implementation of our Front-end Environment for Hands-on Activities (FEHA), which is a web-based programming environment. FEHA provides a programming environment on the web and utilizes existing

-like systems that equip a specialized programming environment as the build and runtime platform. FEHA controls the existing systems by using Secure SHell (SSH) and Rsync without any modification of the existing systems. We discuss a case study of FEHA in which it was applied to actual programming lectures at a university. In the lectures, 70% of the students completed registrations to use FEHA in about 3 min. In addition, they could understand how to use the FEHA and started submitting codes within several minutes after the registration. The case study shows that FEHA is able to provide a specialized programming environment for more than 100 students with a small amount of effort from the instructor and system administrator.

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A journaling file system is a file system that records information about pending updates to the file system before committing the updates. This mechanism raises the reliability of the system because it enables any inconsistencies to be repaired with minimal loss of data. Since there is a tradeoff between the overhead and reliability, ext3, a journaling file system commonly used by the Linux kernel, offers three journaling modes: speed-prioritized mode, reliability-prioritized mode, and intermediate mode. Unfortunately, in ext3, the journaling mode has to be set individually for each file system. Thus, the granularity of the journaling mode setting is very coarse. In addition, the journaling mode must be determined at the time of mounting the file system and cannot be changed without unmounting it. To resolve this problem, this paper proposes a new journaling file system named dajFS (per-directory adaptive journaling file system) that is able to set an appropriate journaling mode for each directory and to switch the journaling mode of a directory to another on the fly without unmounting the file system. Essentially, the journaling mode that is specified for a directory applies to all files that reside directly under that directory. By using dajFS, the user can determine and set a journaling mode for each directory on the basis of the importance of files under that directory. As a result, the user can enjoy moderate granularity with the journaling mode setting.

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In this paper, we propose the use of the server/client system in statistical analysis. We show that the interactive response speed of a time series analysis system TISAS (TIme Series Analysis Supporting system) has been improved by adding functions for distributed processing by using the Parallel Virtual Machine (PVM) library. TISAS was originally designed for building an object-based graphical user interface (GUI). The Tcl/Tk interpreter language was chosen as the main programming language, because it was designed especially for building GUI applications easily. We reconstruct TISAS by adopting a server/client system structure without changing the style of the GUI by using TkPVM, which is an implementation of the PVM library through Tcl/Tk.

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The Log-structured File System (LFS) transforms random writes to a huge sequential one to provide superior performance on storage devices. However, LFS inherently suffers from overhead incurred by cleaning segments. Specifically, when file system utilization is high and the system is busy, performance of LFS degenerates significantly due to high cleaning cost. Also, in the newer flash memory based SSD storage devices, cleaning leads to reduced SSD lifetime as it incurs more writes. In this paper, we propose an enhancement to the original LFS to alleviate the performance degeneration due to cleaning when the system is busy. The new scheme, which we call Slack Space Recycling (SSR), allows LFS to delay on-demand cleaning during busy hours such that cleaning may be done when the load is much lighter. Specifically, it writes modified data directly to invalid areas (slack space) of used segments instead of cleaning on-demand, pushing back cleaning for later. SSR also has the added benefit of increasing the lifetime of the now popular SSD storage devices. We implement the new SSR-LFS file system in Linux and perform a large set of experiments. The results of these experiments show that the SSR scheme significantly improves performance of LFS for a wide range of storage utilization settings and that the lifetime of SSDs is extended considerably.

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We have constructed a parallel cluster consisting of Apple Macintosh G4 computers running both Classic Mac OS as well as the -based Mac OS X, and have achieved very good performance on numerically intensive, parallel plasma particle-in-cell simulations. Unlike other -based clusters, no special expertise in operating systems is required to build and run the cluster. This enables us to move parallel computing from the realm of experts to the mainstream of computing.

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The growth of material and semicondutor technology enable the tremendously increase in disk density. Hard disk capacility has grown from mega-byte capacility to gigibtye and maybe we may even seen terbytpe disk in the near future. With the growth in disk capacity, we also see a increase in volume of data. Getting terabtyes of data in and out of disks is not trivial, especially with realtime requirement. In this paper, we discuss a new system achitecture and file system that is specifically designed to handle large data requirement.

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Edge intelligence (EI), as a combination of artificial intelligence (AI) and internet of things (IoT), is the key to realize an interconnected world of everything. EI needs to process the data collected by edge devices locally. For edge devices with insufficient computing power, a near data computing (NDC) system can provide local computing capability by adding a co-processing unit near the memory. NDC systems are extensively studied focused on the optimization of the hardware architecture but lack of universal and transparent system support. Meanwhile, we notice that non-volatile memory (NVM) plays an important role in edge intermittent computing. In this article, we propose a novel in-memory processing file system (IMPFS) based on NVM to provide general support for NDC system running on edge devices. IMPFS uses standard file system interfaces and is optimized for NVM and AI application management. To verify the IMPFS, a prototype system is designed. The results showed that the IMPFS can not only provide universal support for EI but also further improve the processing speed by reducing the redundant software overhead.

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Multicore processor architectures have become ubiquitous in today's computing platforms, especially in parallel computing installations, with their power and cost advantages. While the technology trend continues towards having hundreds of cores on a chip in the foreseeable future, an urgent question posed to system designers as well as application users is whether applications can receive sufficient support on today's operating systems for them to scale to many cores. To this end, people need to understand the strengths and weaknesses on their support on scalability and to identify major bottlenecks limiting the scalability, if any. As open-source operating systems are of particular interests in the research and industry communities, in this paper we choose three operating systems (Linux, Solaris and FreeBSD) to systematically evaluate and compare their scalability by using a set of highly-focused microbenchmarks for broad and detailed understanding their scalability on an AMD 32-core system. We use system profiling tools and analyze kernel source codes to find out the root cause of each observed scalability bottleneck. Our results reveal that there is no single operating system among the three standing out on all system aspects, though some system(s) can prevail on some of the system aspects. For example, Linux outperforms Solaris and FreeBSD significantly for file-descriptor- and process-intensive operations. For applications with intensive sockets creation and deletion operations, Solaris leads FreeBSD, which scales better than Linux. With the help of performance tools and source code instrumentation and analysis, we find that synchronization primitives protecting shared data structures in the kernels are the major bottleneck limiting system scalability.

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The cost of checkpointing consists of checkpoint over-head and checkpoint latency. The former is the time to stop the process for checkpointing. The latter is the time to complete the checkpointing including background checkpointing which stores memory pages. The large checkpoint latency increases the possibility that the error occurs in back-ground checkpointing, which leads to long rollback distance. The method for small checkpoint latency has not been proposed yet. This paper proposes a checkpointing method which achieves small checkpoint latency. The proposed method divides a checkpoint interval into several subcheckpoint intervals. By using the history of memory page modification in subcheckpoint intervals, the proposed method saves some pages which are not expected to be modified in the rest of checkpoint interval in advance. Computer simulation says that the proposed method can reduce the checkpoint latency by 25% comparing to the existing methods.

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File system workloads are increasing

-heavy. The growing capacity of RAM in modern nodes allows many reads to be satisfied from memory while writes must be persisted to disk. Today's sophisticated local file systems like Ext4, XFS and Btrfs optimize for reads but suffer from workloads dominated by microdata (including metadata and tiny files). In this paper we present an LSM-tree-based file system, RFS, which aims to take advantages of the optimization of LSM-tree to provide enhanced microdata performance, while offering matching performance for large files. RFS incrementally partitions the namespace into several metadata columns on a per-directory basis, preserving disk locality for directories and reducing the amplification of LSM-trees. A -ordered log-structured layout is used to store small files efficiently, rather than embedding the contents of small files into inodes. We also propose an optimization of global bloom filters for efficient point lookups. Experiments show our library version of RFS can handle microwrite-intensive workloads 2-10 times faster than existing solutions such as Ext4, Btrfs and XFS.

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Recently, the need for multimedia devices, such as mobile phones, digital TV, PMP, digital camcorders, digital cameras has increased. These devices provide various services for multimedia file manipulation, allowing multimedia contents playback, multimedia file editing, etc. Additionally, digital TV provides a recorded multimedia file copy to a portable USB disk. However, Linux Ext3 file system, as employed by these devices, has a lot of drawbacks, as it required a considerable amount of time and disk I/Os to store large-size edited multimedia files, and it is hard to access for typical PC users. Therefore, in this paper a design and implementation of an amortized Ext3 with FWAE (Fast Writing-After-Editing) for WinXP-based multimedia applications is described. The FWAE is a fast and efficient multimedia file editing/storing technique for the Ext3 that exploits inode block pointer re-setting and shared data blocks by simply modifying metadata information. Individual experiments in this research show that the amortized Ext3 with FWAE for WinXP not only dramatically improves written performance of the Ext3 by 16 times on average with various types of edited multimedia files but also notably reduces the amount of consumed disk space through data block sharing. Also, it provides ease and comfort to use for typical PC users unfamiliar with Linux OS.

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