THOR: A Versatile Commodity Component of Supercomputer Development
The world's highest energy particle accelerator, the Large Hadron Collider (LHC), is presently being constructed at the European Center for Particle Physics Research (CERN) near Geneva, Switzerland. The planned date for first collisions is 2005. Since the demise of the US Superconducting Super Collider (SSC) in 1993, CERN has essentially become a world laboratory where American, African, European, Asian and Australian physicists work side by side. The LHC will penetrate deeper than ever into the microcosm to recreate the conditions prevailing in the universe just a millionth of a millionth of a second after the big bang when the temperature was ten-thousand-million-million degrees.
Our group is a small part of the team of approximately 1500 physicists, from over 100 institutions around the world, engaged in the construction of the ATLAS (A Toroidal LHC ApparatuS) experiment, one of two general-purpose detectors preparing to take data at the LHC. The experimental environment of ATLAS is punishing. For example, ATLAS has hundreds of thousands of detector channels and must keep up with a collision rate that can give rise to approximately 30 new events every 25 nanoseconds. Also, detectors and their accompanying electronics often must operate in high-radiation environments. It is obvious that the computing requirements in such an arena are, to say the least, demanding. CERN is no stranger to software developments required to solve the unique problems presented by international particle physics. For example, the World Wide Web was initially designed at CERN to help communication among the several hundred members scattered in numerous research institutes and universities.
The particle physicists in our group are involved in two areas which pose large computing problems. The first is in the area of time-critical computing, where the raw rate must be reduced from an event rate of around one gigahertz to about 100Hz by a three-stage, real-time data selection process called triggering. We are involved, along with groups from CERN, France, Italy and Switzerland, in the final stage of triggering, called the Event Filter, that reduces the data rate from 1GB/s to 100MB/s, fully reconstructs the data for the first time and writes the data to a storage medium. It is estimated that this last stage of processing would currently require on the order of a thousand “Pentiums”, if current trends in the development of processor speed continue.
We are also actively involved in simulating the response of the ATLAS detector to the physics processes that will be, or might be, present. This second task is not time-critical, but requires large simulation programs and often many hundreds of thousands of fully simulated events. Neither of these applications requires nodes to communicate during processing.
In order to pursue our research aims in these two areas, we had to develop a versatile system that could function as a real-time prototype of the ATLAS Event Filter and also be able to generate large amounts of Monte Carlo data for modeling and simulation. We needed a cost-effective solution that was scalable and modular, as well as compatible with existing technology and software. Also, because of the time scale of the project, we required a solution with a well-defined and economical upgrade path. These constraints led us inevitably toward a “Beowulf-type” commodity-component multiprocessor with a Linux operating system. The machine we finally developed was called THOR, in keeping with the Nordic nature of the names of similar-type systems such as NASA's Beowulf machine and LOKI at Los Alamos National Laboratory.
During our design discussions on THOR, it soon became clear to us that the benefits of scalability, modularity, cost-effectiveness, flexibility and access to a commercial upgrade path make the commodity-component multiprocessor an effective approach for providing high-performance computing for a myriad of scientific and commercial tasks—capable of being utilized for both time-critical and off-line data acquisition and analysis tasks. The combination of commodity Intel processors with conventional fast Ethernet and a high-speed network/back-plane fabric (Scalable Coherent Interface (SCI) from Dolphin Interconnect Solutions Inc.) enables the THOR machine to run as a cluster of serial processors, or as a fully parallel multiprocessor using MPI. It is also possible to rapidly reconfigure the THOR machine from a fully parallel mode to an all-serial mode, or for mixed parallel-serial use.
In order to demonstrate the basic ideas of the THOR project, a prototype has been constructed. A photograph of a slightly earlier incarnation of THOR is shown in Figure 1. This prototype at present consists of 42 dual Pentium II/III MHz machines (40 450MHz and 44 600MHz processors), each with 256MB of RAM. Each node is connected via a 100Mb/s Ethernet 48-way switch. A 450MHz dual Pentium II computer provides the gateway into the THOR prototype. The prototype has access to 150 gigabytes of disk space via a fast/wide SCSI interface and a 42-slot DDS2 tape robot capable of storing approximately half a terabyte of data. The THOR prototype currently runs under Red Hat Linux 6.1.
Sixteen of the 40 nodes have been connected into a two-dimensional 4x4 torus, using SCI, which allows a maximum bi-directional link speed of 800MB/s. We have measured the throughput of the SCI to be 91MB/s, which is close to the PCI bus maximum of 133MB/s. This maximum will rise when the 64-bit version of the SCI hardware, in conjunction with 64-bit PCI bus widths, are available. The use of SCI on THOR permits the classification of these THOR nodes as a Cache Coherent Non-Uniform Memory Access (CC-NUMA) architecture machine. This 16-node (32-processor) subdivision of the THOR prototype was implemented and tested as a fully parallel machine by a joint team from Dolphin Interconnect Solutions Inc. and THOR in the summer of 1999. A schematic diagram of the THOR Linux cluster is shown in Figure 2.
The THOR prototype described above is now being benchmarked as a parallel and serial machine, as well as being used for active physics research. Researchers have access to full C, C++ and FORTRAN compilers, CERN and NAG numerical libraries and MPI parallel libraries for their research use. We also plan to acquire the recent Linux release of IRIS Explorer for THOR research use in the near future. PBS (a Portable Batch System developed at NASA) has been running on THOR since March, 1999.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide