Raining on the Innovation Parade

By Michael Feldman

August 11, 2011

Conventional wisdom informs us that innovation leads to society’s well-being by fostering things like economic growth and higher living standards. It’s pretty much accepted that technology advancements in industrialization, computers, medical technology, and business practices are the big drivers. Economists also claim that innovation drives a specific aspect of economic strength, called productivity.

Or at least it should. An article this week in Technology Review points out that at least one innovation measure is on the decline. Researchers have noticed that since the 1973, US productivity growth has started to flatten.

Tyler Cowen, Professor of Economics, at George Mason calls it the “The Great Stagnation,” which conveniently is the same title as the book he authored. Cowen and others use a measurement called total factor productivity (TFP), which according to Wikipedia ”accounts for effects in total output not caused by inputs.” Basically it’s a metric for how efficiently the economic inputs are utilized for production. The idea is that this reflects the rate of technological advancement, aka innovation.

The chart below tells the sad tale:

The graphic is from a recent report (PDF) compiled by The Hamilton Project that tries to make some sense of what’s happening to innovation in the US. I have several problems with the report, but most of it is centered on the linkage between this TFP metric and innovation.

Anecdotally, having lived through both the pre-70s and post-70s, I can say with a fair amount of confidence that innovation in the latter era has been a lot more impressive than in the former. And not just innovation, but the rate of innovation.

From post-WWII to the 70s, the biggest advancements were the establishment of personal transportation in the modern automobile and the spread of television as the dominant media. It allowed people and goods to be transported freely across the country — at least where the roads go — and enabled near universal access to entertainment and news from homes. Not bad.

But since the 70s we’ve seen the rise of personal and mobile computing, the internet, genetic sequencing (and molecular-based medicine, in general), as well as my favorite and yours, high performance computing. So today, nearly any type of information accumulated by society can be accessed and manipulated from anywhere. To me, that’s more impressive than a 56 Chevy and a 19-inch black and white.

It also should be pointed out that even useful innovation is often ignored. Obviously in that case, it can’t get reflected in productivity. This may be especially true when the rate of innovation is so high that it’s hard for people or businesses to know when to hop aboard.

Some sectors tend to adopt technology quicker than others. For example, manufacturing and biotech have not embraced HPC with nearly the enthusiasm of say, academia and government research. And on the more personal level, technologies like VoIP, (which, as a Skype user, I can attest is a tremendous productivity booster), has yet to be picked up en masse. The reasons for resisting new technologies can be financial, educational or cultural, but they certainly play a big part in adoption.

Then there’s just the more general question whether innovation can exist independently of an economy’s productivity. Some observers have noticed that the flattening of the TFP slope after 1973 coincides with the US government’s abandonment of Keynesian economic policy (run deficits when the private sector cut back, otherwise run surpluses). The implication here is that productivity is more likely to correlate to government spending habits.

On that note, it might be worthwhile to look at what the government is spending its money on. Certainly we’ve seen funding for defense and entitlements — two areas unlikely to contribute to much to either innovation or productivity — increase substantially in the past four decades. Meanwhile US investments in R&D as a percent of GDP dropped from 2.2 percent in 1964 to about 1 percent today. But that in itself is no guarantee, given that R&D spending was below 1 percent in the 1950s, when TFP was doing just dandy.

Then there’s the observant economist who noticed that the TFP for durable goods actually increased during the past four decades, compared to the pre-70s pace. At the same time, the TFP for non-durable goods, which includes the service sector, actually flattened out (it was never very steep to begin with). Since the service sector has grown disproportionally to the durable goods sector, the overall slope of the TFP has flattened.

That’s not to say we shouldn’t do better in the innovation arena. But I do see the problem more as one of adoption than any perceived decline in innovation itself. Again, HPC users could be viewed as a microcosm of the problem. The technology has a good track record for improving productivity, with enough case studies to choke a modest-sized library. Innovation here comes in many forms — accelerators (GPUs and FPGAs), architectures (clusters, SMP machines, and exotics), and software (MPI, OpenMP, CUDA, OpenCL, and so on). The array of choices is overwhelming to the HPC newbie. Here, as elsewhere, understanding the technology is going to be the key to productivity.

In any case, be wary of reports that claim innovation is in trouble. Economists have a propensity to forecast doom scenarios, which is why economics is often referred to as the dismal science. They also love to uncover correlations like this, since that is the lifeblood of their field. But understanding the interplay between technology, economics and society is a daunting task, filled with variables that, frankly, no one fully understands.

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!

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “pre-exascale” award), parsed out additional information ab Read more…

By Tiffany Trader

Tsinghua Crowned Eight-Time Student Cluster Champions at ISC

June 22, 2017

Always a hard-fought competition, the Student Cluster Competition awards were announced Wednesday, June 21, at the ISC High Performance Conference 2017. Amid whoops and hollers from the crowd, Thomas Sterling presented t Read more…

By Kim McMahon

GPUs, Power9, Figure Prominently in IBM’s Bet on Weather Forecasting

June 22, 2017

IBM jumped into the weather forecasting business roughly a year and a half ago by purchasing The Weather Company. This week at ISC 2017, Big Blue rolled out plans to push deeper into climate science and develop more gran Read more…

By John Russell

Intersect 360 at ISC: HPC Industry at $44B by 2021

June 22, 2017

The care, feeding and sustained growth of the HPC industry increasingly is in the hands of the commercial market sector – in particular, it’s the hyperscale companies and their embrace of AI and deep learning – tha Read more…

By Doug Black

HPE Extreme Performance Solutions

Creating a Roadmap for HPC Innovation at ISC 2017

In an era where technological advancements are driving innovation to every sector, and powering major economic and scientific breakthroughs, high performance computing (HPC) is crucial to tackle the challenges of today and tomorrow. Read more…

At ISC – Goh on Go: Humans Can’t Scale, the Data-Centric Learning Machine Can

June 22, 2017

I've seen the future this week at ISC, it’s on display in prototype or Powerpoint form, and it’s going to dumbfound you. The future is an AI neural network designed to emulate and compete with the human brain. In thi Read more…

By Doug Black

Cray Brings AI and HPC Together on Flagship Supers

June 20, 2017

Cray took one more step toward the convergence of big data and high performance computing (HPC) today when it announced that it’s adding a full suite of big data and artificial intelligence software to its top-of-the-l Read more…

By Alex Woodie

AMD Charges Back into the Datacenter and HPC Workflows with EPYC Processor

June 20, 2017

AMD is charging back into the enterprise datacenter and select HPC workflows with its new EPYC 7000 processor line, code-named Naples, announced today at a “global” launch event in Austin TX. In many ways it was a fu Read more…

By John Russell

Hyperion: Deep Learning, AI Helping Drive Healthy HPC Industry Growth

June 20, 2017

To be at the ISC conference in Frankfurt this week is to experience deep immersion in deep learning. Users want to learn about it, vendors want to talk about it, analysts and journalists want to report on it. Deep learni Read more…

By Doug Black

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Tsinghua Crowned Eight-Time Student Cluster Champions at ISC

June 22, 2017

Always a hard-fought competition, the Student Cluster Competition awards were announced Wednesday, June 21, at the ISC High Performance Conference 2017. Amid wh Read more…

By Kim McMahon

GPUs, Power9, Figure Prominently in IBM’s Bet on Weather Forecasting

June 22, 2017

IBM jumped into the weather forecasting business roughly a year and a half ago by purchasing The Weather Company. This week at ISC 2017, Big Blue rolled out pla Read more…

By John Russell

Intersect 360 at ISC: HPC Industry at $44B by 2021

June 22, 2017

The care, feeding and sustained growth of the HPC industry increasingly is in the hands of the commercial market sector – in particular, it’s the hyperscale Read more…

By Doug Black

At ISC – Goh on Go: Humans Can’t Scale, the Data-Centric Learning Machine Can

June 22, 2017

I've seen the future this week at ISC, it’s on display in prototype or Powerpoint form, and it’s going to dumbfound you. The future is an AI neural network Read more…

By Doug Black

Cray Brings AI and HPC Together on Flagship Supers

June 20, 2017

Cray took one more step toward the convergence of big data and high performance computing (HPC) today when it announced that it’s adding a full suite of big d Read more…

By Alex Woodie

AMD Charges Back into the Datacenter and HPC Workflows with EPYC Processor

June 20, 2017

AMD is charging back into the enterprise datacenter and select HPC workflows with its new EPYC 7000 processor line, code-named Naples, announced today at a “g Read more…

By John Russell

Hyperion: Deep Learning, AI Helping Drive Healthy HPC Industry Growth

June 20, 2017

To be at the ISC conference in Frankfurt this week is to experience deep immersion in deep learning. Users want to learn about it, vendors want to talk about it Read more…

By Doug Black

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference Read more…

By Tiffany Trader

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

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

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

Leading Solution Providers

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of “quantum supremacy,” researchers are stretching the limits of today’s most advanced supercomputers. Read more…

By Tiffany Trader

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" processors. The infrastructure is based on the 68-core Intel Knights Landing processor with integrated Omni-Path fabric (the 7250F Xeon Phi). Read more…

By Tiffany Trader

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