The history of computers is less than a century long, but comparing the machines from a few decades ago with the slick new models of today, it seems like a lot longer. Here’s a fun little flashback to some “ancient” University of Minnesota computers.
To provide some context on the advances in computer technology in the past 50-plus years, consider this excerpt from a press release the University of Minnesota News Service distributed on Sept. 8, 1961.
“The University of Minnesota school of business administration this month will install a $500,000 electronic computer to be used in student training and faculty and graduate student research. The computer, a Univac Solid-State 80, will be given to the University by Remington Rand Univac for joint use by the University in its academic programs and by Remington Rand in training Univac sales and educational personnel.
Dean Grambsch described the Univac Solid-State 80 as a ‘medium-sized’ computer. The seven-unit system includes a central processor, a high-speed card reader, a printer and four tape storage units. It stores 50,000 digits, prints 600 lines per minute and can read data off cards at the rate of 600 words per minute. It carries out computings and data processing operations in millionths of seconds, so fast that it can work a complicated addition problem in only 85/1,000,000 of a second.”
We sent the above excerpt to Jorge Viñals, director of the Minnesota Supercomputing Institute, to get his insights on then vs. now.
“A ‘medium-sized’ smart phone today (at $500) includes two central processors, no card readers, printers or tape, but can store a few billion digits, and read them off at a rate of hundreds of millions of words a second, let alone per minute. A complicated addition problem would take only 1 billionth of a second.
The largest supercomputer on campus (now at about $5 million) has almost 10,000 computing elements — still no card readers, printers or tapes. It can hold approximately 50 trillion digits in memory, and read them off at about 30 billion digits per second. One would not do a single sum on a machine like this, but spread over the entire system, the equivalent time would be 0.00000000000001 seconds per sum.”
Photos courtesy of University of Minnesota Archives, U of M, Twin Cities
Press release excerpt from U of M Digital Conservancy (see the collection)