The Undervalued Tech Worker

By Michael Feldman

November 27, 2008

In our supposedly tech-driven economy, it’s common to hear about computer professionals who have lost their jobs and are unable to find new work in their field. And this was occurring even before the recession. Is the IT industry really that much at odds with its own labor market? Surprisingly, yes.

In a recent InfoWorld advice column hosted by Bob Lewis, a reader talks about an increasingly hostile tech labor marketplace — not only for workers with “legacy” skill sets, but even for those with more recent experience:

[I]t’s not just the COBOL and Fortran programmers, the OS/360 and SCOPE dinosaurs. It’s also the software architects; data-base architects; system and network administrators; PHP, Python, Ruby on Rails, and Objective-C software engineers; and heavy metal engineers who were presenting papers at national and international conferences one day, and pariah the next.

The reader follows up with a familiar observation about the industry’s indifference to providing employment continuity for the workforce:

The industry [executives have] made it clear. [They are] not interested in re-training the current workforce, which is likely adequate for its needs. No, it wants fresh bodies, preferably young or beholden ones willing to accept entry-level wages for long hours and who are either burdened with few family obligations or willing to pass them over… for the most part, companies are unwilling to re-train experienced programmers to fill available slots…

I’ve written about this on a few occasions, myself, in the context of the H-1B visa program for non-U.S. workers. But something else struck me when I read Lewis’ response:

Since I try to avoid recommending solutions that require legislation, and also try to avoid moralizing in my writing, I recommend courses of action based on this being how the world works right now. People are products in the employment marketplace. If someone can’t find a job, that means for one reason or another that person isn’t a competitive product. The problem might be marketing, packaging, pricing, or a perceived lack of quality. Whatever it is, this is no different from any other marketplace — it’s up to the seller to package, price and market a product people want to buy.

Lewis says he’s not unsympathetic to the techie’s plight; he’s just trying to be honest. And he makes a good a point.

But casting people as products is not only demoralizing, it’s wrong-headed, and it reflects some unfortunate attitudes in the IT community. Specifically, the conventional wisdom is that maximizing ROI takes precedence over maximizing innovation. While that philosophy may work in a more mature industry that isn’t subject to a lot of technological turnover, like say bubble gum manufacturing, in the computing business it’s just short-sighted.

Since tech workers are the ones that design hardware, write software, and provide services, under-investing in them has some regrettable effects. The most visible example of this is the permanent “software crisis,” which is currently playing out in the industry’s attempt to apply parallel programming to the new raft of multicore and multiprocessor platforms. Moore’s Law continues to double raw processing power every 18 months or so, but only a fraction of that is realized at the application level. But wasting cheap CPU cycles seems to make more sense than applying more human ingenuity to the problem.

To be fair, firms like Intel and Microsoft, along with help from the government, are investing a ton of money in parallel programming R&D, but most companies are willing to let this be somebody else’s problem. The answer for the industry is going to require the adoption of new software platforms and training (or retraining) workers. And that’s going to filter down to everyone.

The relocation of computing into the cloud is another challenge that’s going to require a lot of new software development, infrastructure buildout, and a whole new industry to service it. Hardware is the easy part. It’s the extra labor that’s going to be the bottleneck. If the IT community convinces itself and its customers that computing will be essentially free once it moves into the cloud, there will be little incentive to invest in human resources to make it happen.

I’m not suggesting that simply retraining old techies is going to be a magic bullet. But there has to be some realization that the industry cannot rely solely on cheap processors, “free” software, and disposable IT workers to create innovation. Ultimately, IT is a labor-intensive industry. The purpose of computer systems is not to eliminate jobs, it’s to create value and increase productivity.

At the Supercomputing Conference and Expo last week, there was a panel discussion on disruptive technologies for exascale systems. It was revealing that the four technologies highlighted were all hardware-focused: flash storage, photonic communications, 3D chip stacking, and quantum computing. It’s easy to become seduced by these inventions. Once they’re designed and implemented, they can be mass-produced, with little human intervention. As expensive as semiconductor fabs are, they can work 24/7 and don’t require health insurance and retirement benefits.

But clever software can make even great hardware humble. D-Wave CTO Geordie Rose, the panel’s quantum computing advocate, argued that new algorithms can have a much bigger payoff than more powerful silicon. He noted that using Pollard’s rho algorithm from 1977, it would take 12 years to factor a 90-digit number on a modern-day 400 teraflop Blue Gene supercomputer. But using the newer quadratic seive algorithm, it would take just 3 years to perform the same operation on a 1977 Apple II computer. When you consider the multi-million dollar investment that went into the Blue Gene supercomputer compared to the probable investment that went into developing the new algorithm, you can get some sense of the industry’s misplaced priorities.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

HOKUSAI’s BigWaterfall Cluster Extends RIKEN’s Supercomputing Performance

February 21, 2018

RIKEN, Japan’s largest comprehensive research institution, recently expanded the capacity and capabilities of its HOKUSAI supercomputer, a key resource managed by the institution’s Advanced Center for Computing and C Read more…

By Ken Strandberg

Neural Networking Shows Promise in Earthquake Monitoring

February 21, 2018

A team of Harvard University and MIT researchers report their new neural networking method for monitoring earthquakes is more accurate and orders of magnitude faster than traditional approaches. Read more…

By John Russell

HPE Wins $57 Million DoD Supercomputing Contract

February 20, 2018

Hewlett Packard Enterprise (HPE) today revealed details of its massive $57 million HPC contract with the U.S. Department of Defense (DoD). The deal calls for HPE to provide the DoD High Performance Computing Modernizatio Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Experience Memory & Storage Solutions that will Transform Your Data Performance

High performance computing (HPC) has revolutionized the way we harness insight, leading to a dramatic increase in both the size and complexity of HPC systems. Read more…

Topological Quantum Superconductor Progress Reported

February 20, 2018

Overcoming sensitivity to decoherence is a persistent stumbling block in efforts to build effective quantum computers. Now, a group of researchers from Chalmers University of Technology (Sweden) report progress in devisi Read more…

By John Russell

HOKUSAI’s BigWaterfall Cluster Extends RIKEN’s Supercomputing Performance

February 21, 2018

RIKEN, Japan’s largest comprehensive research institution, recently expanded the capacity and capabilities of its HOKUSAI supercomputer, a key resource manage Read more…

By Ken Strandberg

Neural Networking Shows Promise in Earthquake Monitoring

February 21, 2018

A team of Harvard University and MIT researchers report their new neural networking method for monitoring earthquakes is more accurate and orders of magnitude faster than traditional approaches. Read more…

By John Russell

HPE Wins $57 Million DoD Supercomputing Contract

February 20, 2018

Hewlett Packard Enterprise (HPE) today revealed details of its massive $57 million HPC contract with the U.S. Department of Defense (DoD). The deal calls for HP Read more…

By Tiffany Trader

Fluid HPC: How Extreme-Scale Computing Should Respond to Meltdown and Spectre

February 15, 2018

The Meltdown and Spectre vulnerabilities are proving difficult to fix, and initial experiments suggest security patches will cause significant performance penal Read more…

By Pete Beckman

Brookhaven Ramps Up Computing for National Security Effort

February 14, 2018

Last week, Dan Coats, the director of Director of National Intelligence for the U.S., warned the Senate Intelligence Committee that Russia was likely to meddle in the 2018 mid-term U.S. elections, much as it stands accused of doing in the 2016 Presidential election. Read more…

By John Russell

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

The Food Industry’s Next Journey — from Mars to Exascale

February 12, 2018

Global food producer and one of the world's leading chocolate companies Mars Inc. has a unique perspective on the impact that exascale computing will have on the food industry. Read more…

By Scott Gibson, Oak Ridge National Laboratory

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

AMD Showcases Growing Portfolio of EPYC and Radeon-based Systems at SC17

November 13, 2017

AMD’s charge back into HPC and the datacenter is on full display at SC17. Having launched the EPYC processor line in June along with its MI25 GPU the focus he Read more…

By John Russell

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Leading Solution Providers

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

Tensors Come of Age: Why the AI Revolution Will Help HPC

November 13, 2017

Thirty years ago, parallel computing was coming of age. A bitter battle began between stalwart vector computing supporters and advocates of various approaches to parallel computing. IBM skeptic Alan Karp, reacting to announcements of nCUBE’s 1024-microprocessor system and Thinking Machines’ 65,536-element array, made a public $100 wager that no one could get a parallel speedup of over 200 on real HPC workloads. Read more…

By John Gustafson & Lenore Mullin

Flipping the Flops and Reading the Top500 Tea Leaves

November 13, 2017

The 50th edition of the Top500 list, the biannual publication of the world’s fastest supercomputers based on public Linpack benchmarking results, was released Read more…

By Tiffany Trader

V100 Good but not Great on Select Deep Learning Aps, Says Xcelerit

November 27, 2017

Wringing optimum performance from hardware to accelerate deep learning applications is a challenge that often depends on the specific application in use. A benc Read more…

By John Russell

SC17: Singularity Preps Version 3.0, Nears 1M Containers Served Daily

November 1, 2017

Just a few months ago about half a million jobs were being run daily using Singularity containers, the LBNL-founded container platform intended for HPC. That wa Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This