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History of computer clusters

History of computer clusters is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand History of computer clusters rather than just read about it. In short: The history of computer clusters is best captured by a footnote in Greg Pfister's In Search of Clusters: "Virtually every press release from DEC mentioning clusters says 'DEC, who invented clusters...'. IBM did not invent them either.

History of computer clusters — main illustration
History of computer clusters — illustration

Key takeaways

  • History of computer clusters belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect History of computer clusters to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of History of computer clusters from memory before moving on to harder problems.

Reference excerpt

The history of computer clusters is best captured by a footnote in Greg Pfister's In Search of Clusters: "Virtually every press release from DEC mentioning clusters says 'DEC, who invented clusters...'. IBM did not invent them either. Customers invented clusters, as soon as they could not fit all their work on one computer, or needed a backup. The date of the first is unknown, but it would be surprising if it was not in the 1960s, or even late 1950s." The formal engineering basis of cluster computing as a means of doing parallel work of any sort was arguably invented by Gene Amdahl of IBM, who in 1967 published what has come to be regarded as the seminal paper on parallel processing: Amdahl's Law. Amdahl's Law describes mathematically the speedup one can expect from parallelizing any given otherwise serially performed task on a parallel architecture. This article defined the engineering basis for both multiprocessor computing and cluster computing, where the primary differentiator is whether or not the interprocessor communications are supported "inside" the computer (on for example a customized internal communications bus or network) or "outside" the computer on a commodity network. Consequently, the history of early computer clusters is more or less directly tied into the history of early networks, as one of the primary motivations for the development of a network was to link computing resources, creating a de facto computer cluster. Packet switching networks were conceptually invented by the RAND corporation in 1962. Using the concept of a packet switched network, the ARPANET project succeeded in creating in 1969 what was arguably the world's first commodity-network based computer cluster by linking four different computer centers (each of which was something of a "cluster" in its own right, but probably not a commodity cluster). The ARPANET project grew into the Internet—which can be thought of as "the mother of all computer clusters" (as the union of nearly all of the compute resources, including clusters, that happen to be connected). It also established the paradigm in use by all computer clusters in the world today—the use of packet-switched networks to perform interprocessor communications between processor (sets) located in otherwise disconnected frames. The development of customer-built and research clusters proceeded hand in hand with that of both networks and the Unix operating system from the early 1970s, as both TCP/IP and the Xerox PARC project created and formalized protocols for network-based communications. The Hydra operating system was built for a cluster of DEC PDP-11 minicomputers called C.mmp at Carnegie Mellon University in 1971. However, it was not until circa 1983 that the protocols and tools for easily doing remote job distribution and file sharing were defined (largely within the context of BSD Unix, as implemented by Sun Microsystems) and hence became generally available commercially, along with a shared filesystem. The first commercial clustering product was ARCnet, developed by Datapoint in 1977. ARCnet was not a commercial success and clustering per se did not really take off until Digital Equipment Corporation released their VAXcluster product in 1984 for the VAX/VMS operating system. The ARCnet and VAXcluster products not only supported parallel computing, but also shared file systems and peripheral devices. The idea was to provide the advantages of parallel processing, while maintaining data reliability and uniqueness. VAXcluster, now VMScluster, is still available on OpenVMS running on Alpha, Itanium and x86-64 systems. Two other noteworthy early commercial clusters were the Tandem Himalaya (a circa 1994 high-availability product) and the IBM S/390 Parallel Sysplex (also circa 1994, primarily for business use). No history of commodity computer clusters would be complete without noting the pivotal role played by the development of Parallel Virtual Machine (PVM) software in 1989. This open source software based on TCP/IP communications enabled the instant creation of a virtual supercomputer—a high performance compute cluster—made out of any TCP/IP connected systems. Free-form heterogeneous clusters built on top of this model rapidly achieved total throughput in FLOPS that greatly exceeded that available even with the most expensive "big iron" supercomputers. PVM and the advent of inexpensive networked PCs led, in 1993, to a NASA project to build supercomputers out of commodity clusters. In 1995 the Beowulf cluster—a cluster built on top of a commodity network for the specific purpose of "being a supercomputer" capable of performing tightly coupled parallel HPC computations—was invented, which spurred the independent development of grid computing as a named entity, although Grid-style clustering had been around at least as long as the Unix operating system and the Arpanet, whether or not it, or the clusters that used it, were named.

See also History of supercomputing

References

Illustrations

History of computer clusters: A VAX 11/780, c. 1977
A VAX 11/780, c. 1977

Worked examples

Example 1 — a first encounter with History of computer clusters

Start with the simplest possible case. Write down what History of computer clusters claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to History of computer clusters before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about History of computer clusters ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of History of computer clusters

In research
History of computer clusters appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses History of computer clusters in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
History of computer clusters is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cluster computing, Concurrent computing, History of computing hardware, so understanding it makes those chapters shorter.
In everyday life
Look for History of computer clusters outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study History of computer clusters in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what History of computer clusters means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain History of computer clusters out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is History of computer clusters in simple terms?

The history of computer clusters is best captured by a footnote in Greg Pfister's In Search of Clusters: "Virtually every press release from DEC mentioning clusters says 'DEC, who invented clusters...'. IBM did not invent them either.

Why does History of computer clusters matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study History of computer clusters?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on History of computer clusters.

Tags

  • Cluster computing
  • Concurrent computing
  • History of computing hardware
  • Parallel computing

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