Pentium Farm is a project involving 10 Linux SMP Pentiums connected to act as a cluster for parallel proccessing. The System became operational august 1996.
This system is used primarily for research and educational activities. Currently using PVM, MPI,POSIX threads and other tools.
A cooperation between the Interdisciplinary Center for Scientific Computing at the University of
Heidelberg (IWR) and the Computing Center of the University of Mannheim
(RUM). Within this cooperation we provide interessted scientists of the IWR
and the University of Mannheim with a Pentium Pro Cluster connected by fast
Myrinet communication hardware.
Linux is a freely-distributable implementation of UNIX for x86, Motorola 68k, Digital Alpha and Motorola PowerPC machines.
Linux was originally written by Linus Torvalds, in Helsinki, Finland. After over 2 years, Linux has become one of the most popular free unixes available, and is continually being developed by Linus and teams of people all around the world.
Linux has all the features you would expect in a modern fully-fledged Unix, including true
multitasking, virtual memory, shared libraries, demand loading, shared copy-on-write executables, proper memory management, TCP/IP networking, symmetric multi-processing, etc.
SMP (Symmetric Multi-Processor) refers to the operating system concept of a group of processors working together as peers, so that any piece of work could be done equally well by any processor. Typically, SMP implies the combination of MIMD and shared memory.
The current ix86 kernel supports Intel MP v1.1 and Intel MP v1.4 compliant motherboards with between 1 and 16 486/Pentium/Pentium Pro processors in which multiple processors share a single memory and bus interface within a single computer.
For more details about Linux, SMP and related topics click here. The most up-to-date information on SMP Linux is probably available via the SMP Linux project mailing list; send email to firstname.lastname@example.org
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Parallel Processing refers to the concept of speeding-up the execution of a program by dividing the program into multiple fragments that can execute simultaneously, each on its own processor. A program being executed across n processors might execute n times faster than itwould using a single processor. Here are some links related to the practice and theory of parallel computing.
A variety of industrial applications are well suited for parallelisation because they deal with problems that can easily be divided into sub-problems. This applies especially to manytypes of analysis and simulation.
PVM (Parallel Virtual Machine) will permit a heterogeneous collection of
Unix computers hooked together by a network to be used as a single large parallel computer.Thus large computational problems can be solved more cost effectively by using the aggregate power and memory of many computers.