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Модуль 6. Текст «IBM Blue Gene»
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IBM Blue Gene. The world's most advanced network supercomputer from International Business Machines will tackle Grand Challenge problems.
Why Supercomputers are fast.Several elements of a supercomputer contribute to its high level of performance:
· Numerous high-performance processors (CPUs) for parallel processing
· Specially-designed high-speed interconnects (internal networks)
· Specially-designed or tuned operating systems
Supercomputer Processors. Supercomputers utilize either custom or mainstream commercial microprocessors. Small supercomputers may contain only a few dozen processors, but today's fastest supercomputers incorporate thousands of processors. The table below summarizes the processor configuration of today's top supercomputers.
| System | Processor Configuration |
| ASCI Red | 9,472 Intel Pentium II Xeon |
| ASCI Blue Pacific | 5,856 IBM PowerPC 604E |
| ASCI White | 8,192 IBM Power3-II |
| NEC Earth Simulator | 5,104 NEC vector processors |
Some supercomputer designs feature network co-processors. When sending and receiving data at the rate necessary for high-performance networking, it's common for a single processor to become heavily loaded with communications interrupts that take away too many cycles from primary computing tasks. To solve this problem, the IBM Blue Gene system will utilize cells. Each cell contains a primary processor, a network co-processor, and shared on-chip memory.
In total, the IBM Blue Gene system will contain one million custom IBM processors. So that the system will fit within a reasonably-sized room and not consume too much power, the processors are engineered so small that 32 of them will fit on a single microchip.
Supercomputer Interconnects. In order for a large number of processors to work together, supercomputers utilize specialized network interfaces. These interconnections support high bandwidth and very low latency communication.
Interconnects join nodes inside the supercomputer together. A node is a communication endpoint running one instance of the operating system. Nodes utilize one or several processors and different types of nodes can exist within the system. Compute nodes, for example, execute the processes and threads required for raw computation. I/O nodes handle the reading and writing of data to disks within the system. Service nodes and network nodes provide the user interface into the system and also network interfaces to the outside world. Special-purpose nodes improve overall performance by segregating the system workload with hardware and system software configured to best handle that workload.
Supercomputer nodes fit together into a network topology. Modern supercomputers have utilized several different specialized network topologies including hypercube, two-dimensional and three-dimensional mesh, and torus. Supercomputer network topologies can be either static (fixed) or dynamic (through the use of switches).
More on Supercomputer Interconnects. Supercomputers utilize various network protocols. Application data communications generally take place at the physical and data link layers. I/O and communications with external networks utilize technologies like HIPPI, FDDI, and ATM as well as Ethernet.
Supercomputer interconnects involve large quantities of network cabling. These cables can be very difficult to install as they often must fit within small spaces. Supercomputers do not utilize wireless networking internally as the bandwidth and latency properties of wireless are not suitable for high-performance communications.
Supercomputer Operating Systems. Many supercomputers run multiple copies of a UNIX-based operating system. The ASCI White and Blue Pacific systems, for example, run IBM AIX. In the 1990s, research into high-performance network operating systems led to the development of so-called «lightweight» operating systems (O/Ses) that consist of a small, simple kernel with many of the capabilities of a general-purpose O/S removed. The ASCI Red system runs the PUMA O/S on its compute nodes.
Модуль 7. Текст «Вычислительная архитектура кластерных сетей»
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3. Составьте аннотацию.
4. Подготовьте пересказ текста.
Cluster Network Computing Architecture. The topic of clustering draws a fair amount of interest from the computer networking community, but the concept is a generic one. To use a non-technical analogy: saying you are interested in clustering is like saying you are interested in food. Does your interest lie in cooking? In eating? Perhaps you are a farmer interested primarily in growing food, or a restaurant critic, or a nutritionist. As with food, a good explanation of clustering depends on your situation.
Not This Kind. The computing world uses the term «clustering» in at least two distinct ways. For one, «clustering» or «cluster analysis» refers to algorithmic approaches of determining similarity among objects. This kind of clustering might be very appealing if you like math... but this is not the sort of clustering we mean in the networking sense.
What Is Cluster Computing? In a nutshell, network clustering connects otherwise independent computers to work together in some coordinated fashion. Because clustering is a term used broadly, the hardware configuration of clusters varies substantially depending on the networking technologies chosen and the purpose (the so-called «computational mission») of the system. Clustering hardware comes in three basic flavors: so-called «shared disk», «mirrored disk», and «shared nothing» configurations.
Shared Disk Clusters. One approach to clustering utilizes central I/O devices accessible to all computers («nodes») within the cluster. We call these systems shared-disk clusters as the I/O involved is typically disk storage for normal files and/or databases. Shared-disk cluster technologies include Oracle Parallel Server (OPS) and IBM's HACMP.
Shared-disk clusters rely on a common I/O bus for disk access but do not require shared memory. Because all nodes may concurrently write to or cache data from the central disks, a synchronization mechanism must be used to preserve coherence of the system. An independent piece of cluster software called the «distributed lock manager» assumes this role.
Shared-disk clusters support higher levels of system availability: if one node fails, other nodes need not be affected. However, higher availability comes at a cost of somewhat reduced performance in these systems because of overhead in using a lock manager and the potential bottlenecks of shared hardware generally. Shared-disk clusters make up for this shortcoming with relatively good scaling properties: OPS and HACMP support eight-node systems, for example.
Shared Nothing Clusters. A second approach to clustering is dubbed shared-nothing because it does not involve concurrent disk accesses from multiple nodes. (In other words, these clusters do not require a distributed lock manager.) Shared-nothing cluster solutions include Microsoft Cluster Server (MSCS).
MSCS is an atypical example of a shared nothing cluster in several ways. MSCS clusters use a shared SCSI connection between the nodes, which naturally leads some people to believe this is a shared-disk solution. But only one server (the one that owns the quorum resource) needs the disks at any given time, so no concurrent data access occurs. MSCS clusters also typically include only two nodes, whereas shared nothing clusters in general can scale to hundreds of nodes.
Mirrored Disk Clusters. Mirrored-disk cluster solutions include Legato's Vinca. Mirroring involves replicating all application data from primary storage to a secondary backup (perhaps at a remote location) for availability purposes. Replication occurs while the primary system is active, although the mirrored backup system – as in the case of Vinca – typically does not perform any work outside of its role as a passive standby. If a failure occurs in the primary system, a failover process transfers control to the secondary system. Failover can take some time, and applications can lose state information when they are reset, but mirroring enables a fairly fast recovery scheme requiring little operator intervention. Mirrored-disk clusters typically include just two nodes.
Conclusion. Network clusters offer a high-performance computing alternative to SMP and massively parallel computing systems. Aggregate system performance aside, cluster architectures also can lead to more reliable computer systems through redundancy. Choosing hardware architecture is just the beginning step in building a useful cluster: applications, performance optimization, and system management issues must also be handled.
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