In pioneer days they used oxen for heavy pulling, and when one ox couldn't budge a log, they didn't try to grow a larger ox. We shouldn't be trying for bigger computers, but for more systems of computers.
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Analogy explaining the need for distributed computing systems rather than just larger single computers.
Date: 1987 (OCLC Newsletter, March/April)
GeneralFound in 1 providers: gemini
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This advocates for distributed computing over scaling up a single machine. Instead of building one massive, powerful computer, we should connect networks of multiple smaller ones working together. The ox analogy makes the point intuitive: when a task exceeds one unit's capacity, the answer is parallelism and collaboration, not brute-force enlargement. It champions horizontal scaling—adding more nodes—over vertical scaling—making one node bigger and more expensive.
Hopper spent decades with early mainframes at Remington Rand and the Navy, witnessing how single-machine bottlenecks limited computing's reach. She championed COBOL precisely because it ran across different systems, not just one powerful machine. Her career centered on making computing portable and practical—standardized compilers, machine-independent languages—tools enabling cooperation between systems rather than concentrating power in one giant machine.
Hopper made this observation during the mainframe era, when IBM and competitors raced to build ever-larger single machines. The Cold War funneled massive government investment into raw computing power concentrated in huge systems. Meanwhile ARPANET was emerging, demonstrating that networked machines could outperform isolated giants. Her framing anticipated distributed computing, server clusters, and ultimately the internet—radical thinking when 'get a bigger machine' was the industry's default answer to every performance ceiling.
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