Java For High-performance Computing Research Articles

Java in the High Performance Computing arena: Research, practice and experience

The rising interest in Java for High Performance Computing (HPC) is based on the appealing features of this language for programming multi-core cluster architectures, particularly the built-in networking and multithreading support, and the continuous increase in Java Virtual Machine (JVM) performance. However, its adoption in this area is being delayed by the lack of analysis of the existing programming options in Java for HPC and thorough and up-to-date evaluations of their performance, as well as the unawareness on current research projects in this field, whose solutions are needed in order to boost the embracement of Java in HPC.This paper analyzes the current state of Java for HPC, both for shared and distributed memory programming, presents related research projects, and finally, evaluates the performance of current Java HPC solutions and research developments on two shared memory environments and two InfiniBand multi-core clusters. The main conclusions are that: (1) the significant interest in Java for HPC has led to the development of numerous projects, although usually quite modest, which may have prevented a higher development of Java in this field; (2) Java can achieve almost similar performance to natively compiled languages, both for sequential and parallel applications, being an alternative for HPC programming; (3) the recent advances in the efficient support of Java communications on shared memory and low-latency networks are bridging the gap between Java and natively compiled applications in HPC. Thus, the good prospects of Java in this area are attracting the attention of both industry and academia, which can take significant advantage of Java adoption in HPC.

Device level communication libraries for high-performance computing in Java

Since its release, the Java programming language has attracted considerable attention from the high-performance computing (HPC) community because of its portability, high programming productivity, and built-in multithreading and networking support. As a consequence, several initiatives have been taken to develop a high-performance Java message-passing library to program distributed memory architectures, such as clusters. The performance of Java message-passing applications relies heavily on the communications performance. Thus, the design and implementation of low-level communication devices that support message-passing libraries is an important research issue in Java for HPC. MPJ Express is our Java message-passing implementation for developing high-performance parallel Java applications. Its public release currently contains three communication devices: the first one is built using the Java New Input/Output (NIO) package for the TCP/IP; the second one is specifically designed for the Myrinet Express library on Myrinet; and the third one supports thread-based shared memory communications. Although these devices have been successfully deployed in many production environments, previous performance evaluations of MPJ Express suggest that the buffering layer, tightly coupled with these devices, incurs a certain degree of copying overhead, which represents one of the main performance penalties. This paper presents a more efficient Java message-passing communications device, based on Java Input/Output sockets, that avoids this buffering overhead. Moreover, this device implements several strategies, both in the communication protocol and in the HPC hardware support, which optimizes Java message-passing communications. In order to evaluate its benefits, this paper analyzes the performance of this device comparatively with other Java and native message-passing libraries on various high-speed networks, such as Gigabit Ethernet, Scalable Coherent Interface, Myrinet, and InfiniBand, as well as on a shared memory multicore scenario. The reported communication overhead reduction encourages the upcoming incorporation of this device in MPJ Express (). Copyright © 2011 John Wiley & Sons, Ltd.

Java and Grande applications

Soon after Java became popular for Internet applications, many other fields began looking at it. While Java's original thrust was client-side applets, today its dominant use is in large enterprise servers running business middleware. Its original client-side use is of secondary importance. Java for high-performance computing has been a popular issue and the subject of annual workshops over the last seven years, including the latest event, Java Grande ISCOPE, JGI'02, (http://charm.cs.uiuc.edu/javagrandeIscope/) held in Seattle from 3-5 November 2002. This meeting series joined forces with the International Symposium on Computing in Object-Oriented Parallel Environments (ISCOPE), aimed primarily at object-oriented methods in science and engineering with an emphasis on the use of C++.

High-Performance Cluster Computing. Volume 1: Architecutes and Systems. Volume 2: Programming and Applications

Edited by: Rajkumar Buyya Prentice Hall PTR, Upper Saddle River, NJ, 1999 Volume 1: 881pp, ISBN 0-13-013784-7, $54.00 Volume 2: 700pp, ISBN 0-13-013786-5, $54.00 I used the two books as part of a course that I taught at IIT Delhi during July-Dec 1999. The course was called Special Topics in Computers and included Masters students from the Departments of Electrical Engineering and Computer Science. The idea behind the course was to introduce elements of Distributed and Clustered Computing to students who already have some background in Computer Architecture. In my opinion, a single course in Computer Architecture at the Masters level cannot do justice to the developments that have taken place in this exciting field over the past decades. I have been teaching Computer Architecture at IIT Delhi for about 8 years now and find that the number of topics that I have to include in the course has been increasing very quickly over the years! In 1992, when I first taught the course, I used to teach about Pipelined Computers, Systolic Arrays, SIMD array processors, and Multiprocessors. As time has passed, it has become necessary to include topics such as high-performance interconnection networks, wormhole routing, cache coherence protocols, instruction pipelines, superscalar processors, and instruction-level parallelism. More recently, I have realized that it is also necessary to teach elements of distributed computing and clustered computing. I believe that a course on selected topics from distributed and clustered computing is essential to all branches of Engineering today. High-performance computing is essential to all branches of Engineering, and high-performance clustered computing on clusters of workstations/PCs makes a lot of economical sense. A course such as this is interesting because it is easy for the students to practice what is taught in such a class without too many infrastructures. This makes the course very exciting to students. When I taught parallel algorithms in my class, I could not ask my students to develop these algorithms for lack of good infrastructure. However, a cluster of workstations and PCs is available in almost every University today. Distributed computing is highly popular with students. Students are eager to learn Java and network programming. Rajkumar Buyya's edited volumes have arrived at the right time to provide the right kind of teaching material for the type of course, which I have above mentioned. The first volume covers architectural and system-level issues of clustered computing systems. It has 36 chapters organized into four sections, spanning 811 pages. Section I develops the motivation for high-performance clustered computing. Section II introduces various networking protocols and I/O mechanisms that are useful in clustered computing. Section III covers OS issues such as process scheduling and load balancing. Section IV includes a number of case studies of existing systems. The editor has made a considerable effort in gathering learning material for the volume. I think that this volume could be an excellent text for an advanced course on Computer Architecture. In the course that I taught, I used parts of Section I and IV. To me, the second volume proved more useful. The second volume concerns with applications of clustered computing and applications programming. It is divided into 3 sections. There are 29 chapters that span 604 pages. Both volumes have carefully prepared Glossaries and Indexes. The first section of the second volume is on various programming environments and development tools. Although I limited myself to the discussion of the Parallel Virtual Machine (PVM) and Message Passing Interface (MPI), the editor has also included entire chapters on linking of these two environments, active objects, component-based approach, LiPS, and WebOS. There is a chapter of debugging parallelized code that can be highly valuable for students and developers of applications. The second section is on Java for high-performance computing. These topics raised a lot of interest among students when I taught the course. The third section is on specific algorithms and applications such as parallel genetic algorithms, parallel simulation, distributed database systems, graphics and image processing. The authors who have contributed to the two volumes are all known experts in the areas of Computer Architecture, Computer Networks, Distributed Computing, and Operating Systems. The authors and the editor must be congratulated on this extraordinary effort to compile so much useful material under one place. The books can not only serve as reference material to professional programmers in the modern IT industry, it can also serve as excellent teaching material for courses related to Computer Architecture, Distributed Computing, and Operating Systems. The web page that the editor has created for the book is also a wonderful repository of learning material available on the web. I recommend these volumes wholeheartedly to all serious researchers and students interested in the areas of high-performance computing in general and clustered computing in particular. C. P. Ravikumar, IIT Delhi