The Leading Source for Global News and Information Covering the Ecosystem of High Productivity Computing
March 31, 2006
Back to the future
Technology convergence and consolidation is a natural part of industry's evolution. The storage arena provides a very recent example. Distributed computing storage used to be primarily based on direct attached storage. A disk physically attached to the server bus represented the vast majority of storage. As distributed environments began to grow this configuration became a real challenge. Multiple discrete disks could not meet the performance and image sizes needed for big applications, the necessary software adjuncts added significant ownership costs, and the management burden became overbearing as backups and security auditing was very time consuming. This drove the emergence of Storage Area Networks (SAN) and Network Attached Storage (NAS) devices that allowed commodity disks, robust communications gear and management functionality delivered to the market as an entire system from vendors such as EMC, Hitachi, DataDirect Networks and Network Appliance.
Computing and communications convergence
Distributed computing servers are on the march towards being highly centralized. In an effort to increase computing density and simplify administration, consolidated rack mounted servers became a logical alternative. Over the past 18 months, the industry has moved towards even denser configurations with blade servers.
A blade server is architecturally identical to a rack mount or a tower server but with a different form factor. The main differentiator for a blade is the shared power infrastructure and common management software across blade elements. Blades are interesting to some enterprise customers because they reduce data center footprint and provide more homogeneous configurations.
High performance computing (HPC) users view tower servers, rack mount servers and blades as essentially the same offering from a compute power perspective. All three of these server architectures can be used as a clustered resource. All that is required is a job scheduler to distribute MPI, UPC or other parallelized codes over the compute nodes.
New processors from vendors such as AMD offer a tremendous increase in compute power and flexibility by allowing a more scalable compute infrastructure to be built. Powerful technologies such as AMD's HyperTransport provide the foundation to build high bandwidth, interprocessor communications, low latency clusters and extended coherent memory configurations. The challenges facing many HPC users is unlocking this power and eliminating the underlying communications bottlenecks and control limitations imposed by legacy server architectures.
Standards based high performance interfaces such as HyperTransport, has created a convergence opportunity to directly connect multi-core processor interfaces into a high performance, fault tolerant interconnect. This convergence eliminates an entire set of performance bottlenecks, consolidates many functions and redefines existing boundaries related to scalability, system control and total cost of system ownership.
Adjunct interconnects have big limitations
While clusters present the promise of being able to improve distributed scalable computing, the biggest challenge with clusters is also the characteristic that defines them. In order to get the maximum output from a large set of independent compute resources, the communications between them must be very low latency and never create a performance bottleneck. Unfortunately, current adjunct interconnect mechanisms are limited in bandwidth and cause programmers to have to cope with limited connectivity inside a cluster. IBM and the Department of Energy recognized these limitations and embarked on the Blue Gene project to overcome performance and scalability issues with adjunct interconnects.
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