Python Snakes Its Way Into HPC

By Nicole Hemsoth

November 17, 2010

Interpreted programming languages usually don’t find too many friends in high performance computing. Yet Python, one of the most popular general-purpose interpreted languages, has garnered a small community of enthusiastic followers. True believers got the opportunity to hear about the language in the HPC realm in a tutorial session on Monday and a BoF session on Wednesday. Argonne National Lab’s William Scullin, who participated in both events, talked with HPCwire about the status of Python in this space and what developers might look forward to.

HPCwire: Python is not a language normally associated with high performance or scientific computing. What does it have to offer this user community not being fulfilled by traditional languages, like C, Fortran or other high productivity, interpreted languages like MATLAB?

William Scullin: In a way, Python’s growing adoption in the high performance and scientific computing space is a homecoming. Guido Van Rossum originally began Python as a way of providing an administrative scripting language for the Amoeba distributed operating system. Then as now, it combines simple, easy to learn and maintain syntax with access to the same powerful libraries and function calls you would find in any C or Fortran implementation. While there has always been an emphasis on reducing the time it takes to perform a computation, Python has truly shined in improving scientific computing by taking the work out of programming and reducing the time to solution.

Often, projects fail when they try to be all things to all people. MATLAB, Mathematica, SPSS, and Maple are all very useful tools, in part because they are focused on meeting the needs of a well funded community with very specific goals. Python, arising from a very diverse community that ranges from astrophysicists to game programmers to web designers to entry level computer science students, has been very successful due to the diversity of users. The standard library has become amazingly extensive without becoming inconsistent.

Likewise, the amount of software that has come out of the community is amazing, most of which is open source, and the vast majority of which follows the same coding guidelines as the core modules. This makes it possible to easily develop an interface to an embedded microcontroller to turn off the desk lamp when your simulation finally ends and automatically push results to a web server in less than an hour — or alternately turn on a coffee pot and resubmit your job when the simulation fails — all in one language.

HPCwire: Obviously, performance is a driving issue in HPC. How is the issue of execution performance being addressed?

Scullin: Performance is a matter of perspective. A favorite maxim in the Python community is that the greatest performance improvement comes from going to the working from the non-working state. A second maxim, from Knuth, is that premature optimization is the root of all evil. While the execution speed of a Python application may not be as fast as one written in C, C++, or Fortran, its ease of use and low learning curve sharply improves overall time to solution. It’s a question of developer time versus compute time.

Side stepping the issue, it’s ridiculously easy to extend Python with modules written in C, C++, and Fortran. It’s common in our community to utilize compiled high performance numerical kernels, then use Python to handle areas like I/O, workflow management, computational analysis, and steering. When areas become performance bottlenecks, those areas tend to be rewritten in C.

Conversely, I’ve seen C and Fortran projects where code complexity has prevented maintenance and functionality, leading to thousands of lines of compiled code being replaced with less than a hundred lines of Python. In many ways, Python is coming to fulfill the roles that frameworks like Cactus and Samurai sought to fill at the start of the decade — letting scientists worry about their problems while letting the language and interpreter do the heavy lifting.

HPCwire: Do you think a compiled implementation of Python would be a step in the right direction?

Scullin: There will always be a place for the interpreted reference implementation, especially in development, but if a Python compiler comes along that provides better performance without compromising the language, I can’t see it finding much resistance.

That said, there are currently projects such as Unladen Swallow, PyPy, Stackless Python, Jython, and Iron Python that provide alternatives to the CPython interpreter. Unladen Swallow, backed in part by Google, and PyPy both seek to close the performance gap with compiled languages. Unladen Swallow is particularly exciting as it’s backended into the Low Level Virtual Machine, which is the basis for multiple compilers including Clang, currently the default compiler under Apple’s OS X. This makes a Python compiler more a matter of when than if.

HPCwire: Can you describe some of the more important Python initiatives — language extensions, libraries, tools, etc. — that are aimed at the HPC domain?

Scullin: I cannot speak highly enough of NumPy, which is almost the Swiss army knife of Python for scientific and high performance computing. It’s been under active development for years now with each release providing better performance, automatic integration of popular high performance libraries like BLAS and LAPACK, more features, and greater portability. NumPy is further extended by SciPy, which provides additional tools and lab kits addressing almost every science domain.

Likewise, I think very highly of mpi4py, PyMPI, PyCUDA and its sister PyOpenCL, petsc4py, and PyTrilinos. All of these keep improving the options we have to accelerate our code using the very same tools and interfaces that are available through traditional compiled languages with none of the complexity.

HPCwire: Are there vendors out there with commercially-supported solutions?

Scullin: Indeed, and more importantly, most of them are active contributors to and supporters of the Python community. I can no longer count the number of consulting firms that provide Python solutions. It’s also been very encouraging seeing vendors add Python support to their products. Two companies well known in the HPC space, Rogue Wave and ParaTools, have both been very responsive.

Rogue Wave has provided access to their mathematical libraries, IMSL via PyIMSL. Furthermore, they have brought a number of people into the Python community via PyIMSL Studio which they market officially as a prototyping tool. I’ve encountered PyIMSL studio users so happy with their prototype Python applications with PyIMSL Studio, that they ran with the Python code as production code. I should also mention that while the TotalView debugger is not officially a Python tool, it’s seen a lot of use by Python HPC users and it will be interesting to see where it goes since Rogue Wave’s acquisition of Acumen.

ParaTools, a major contributor to the TAU Performance System and a leading consultant in the area of parallel and high performance codes has done a very good job of adding Python support to TAU.

Without hesitation, I have used their tools with C, Fortran, and Python and found their support to be helpful and responsive regardless of language.

While not directly in the HPC market, Enthought, deserves special mention. They host an array of Python projects with engineering and science applications. They provide a commercial packaging of the Python interpreter with commonly used libraries and utilities along with technical support as the Enthought Python Distribution. Most of all, they are active developers of NumPy and SciPy. Without their support and involvement, I am not sure that NumPy would have come together as nicely as it has.

While relatively new, I’ll also be interested to see what the future holds for MBA Sciences’s SPM.Python toolkit for bringing parallelism into serial Python programs. I’ll be keeping a close watch on PiCloud, a firm which provides an amazingly easy to user cloud computing platform that makes running Python codes on a compute cloud ridiculously easy. PiCloud users have their computations offloaded without any serious code changes, having to be involved in any aspect of setting up a cloud infrastructure, or doing any server management. They’ve seriously made it as simple as coding and running.

Finally, though it hasn’t been making a lot of noise lately, NVIDIA has been putting effort behind Copperhead, which while not a complete Python, allows for the rapid development of CUDA kernels in Python-like code.

HPCwire: Do you think most uses of Python in HPC will eventually involve either integration with C or Fortran or source code translation to those languages?

Scullin: I believe that HPC users will continue to choose the best possible tool to address a need in a given situation. Python is flexible enough that there will be continued integration with C, Fortran, and other languages. At the same time, interpreter performance is being rapidly addressed, which makes the issues that come with language translation into C and Fortran cause that sort of project to be less attractive to active Python developers. What will be interesting to watch is how codes written in a mix of C, C++, Fortran, Python and other languages perform and evolve as the LLVM platform continues to mature.

HPCwire: Can you point to any successful case studies or projects where Python has been employed in this arena?

Scullin: At Argonne, we are involved in the development of GPAW, a density-functional theory Python code based on the projector-augmented wave method. Originating out of an international collaboration, it is mostly a mix of C and Python with the vast majority of the code being Python. It has been run at scale successfully and routinely on our Blue Gene platform. While the porting of any application to platforms like the Cray XT series or the Blue Gene is an interesting exercise in computer science, it’s far more remarkable that the performance has been on par from what I’ve seen in C or C++ codes. Moreover, it is being used to produce reliable data used to generate publications.

The other community that a lot of people think of when looking for successful Python applications in the HPC space is bioinformatics. While I’ve not been involved with many bioinformatics codes, the last four or five years have seen a rising number of chemists and biologists appearing on Python-related mailing lists and at conferences discussing how they have been using Python to power their science. While Perl still holds sway in the field, Python is quickly becoming almost as popular.

HPCwire: For those HPC developers interested in learning more about what’s available in the Python ecosystem, can you point to some resources they could tap into?

Scullin: Depending on their particular interests, one of the best places to start is by visiting www.scipy.org. From there, you can find links to numerous mailing lists, information about conferences, code recipes, documentation, and much more. In the Chicago and Bay Areas there are very active Python users groups with sizable memberships with an interest in HPC and scientific computing. Finally, given Python’s ease of use, one of the best things you can do is to spend an afternoon with the interpreter, simply playing with code and seeing what the language can do for you without any effort. The joy of doing powerful things with simple code is one of the most admirable traits of the language.

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!

University of Stuttgart Inaugurates ‘Hawk’ Supercomputer

February 20, 2020

This week, the new “Hawk” supercomputer was inaugurated in a ceremony at the High-Performance Computing Center of the University of Stuttgart (HLRS). Officials, scientists and other stakeholders celebrated the new sy Read more…

By Staff report

US to Triple Its Supercomputing Capacity for Weather and Climate with Two New Crays

February 20, 2020

The blizzard of news around the race for weather and climate supercomputing leadership continues. Just three days after the UK announced a £1.2 billion plan to build the world’s largest weather and climate supercomputer, the U.S. National Oceanic and Atmospheric Administration... Read more…

By Oliver Peckham

Indiana University Researchers Use Supercomputing to Model the State’s Largest Watershed

February 20, 2020

With water stressors on the rise, understanding and protecting water supplies is more important than ever. Now, a team of researchers from Indiana University has created a new climate change data portal to help Indianans Read more…

By Staff report

TACC – Supporting Portable, Reproducible, Computational Science with Containers

February 20, 2020

Researchers who use supercomputers for science typically don't limit themselves to one system. They move their projects to whatever resources are available, often using many different systems simultaneously, in their lab Read more…

By Aaron Dubrow

China Researchers Set Distance Record in Quantum Memory Entanglement

February 20, 2020

Efforts to develop the necessary capabilities for building a practical ‘quantum-based’ internet have been ongoing for years. One of the biggest challenges is being able to maintain and manage entanglement of remote q Read more…

By John Russell

AWS Solution Channel

Challenging the barriers to High Performance Computing in the Cloud

Cloud computing helps democratize High Performance Computing by placing powerful computational capabilities in the hands of more researchers, engineers, and organizations who may lack access to sufficient on-premises infrastructure. Read more…

IBM Accelerated Insights

Intelligent HPC – Keeping Hard Work at Bay(es)

Since the dawn of time, humans have looked for ways to make their lives easier. Over the centuries human ingenuity has given us inventions such as the wheel and simple machines – which help greatly with tasks that would otherwise be extremely laborious. Read more…

New Algorithm Allows PCs to Challenge HPC in Weather Forecasting

February 19, 2020

Accurate weather forecasting has, by and large, been situated squarely in the domain of high-performance computing – just this week, the UK announced a nearly $1.6 billion investment in the world’s largest supercompu Read more…

By Oliver Peckham

US to Triple Its Supercomputing Capacity for Weather and Climate with Two New Crays

February 20, 2020

The blizzard of news around the race for weather and climate supercomputing leadership continues. Just three days after the UK announced a £1.2 billion plan to build the world’s largest weather and climate supercomputer, the U.S. National Oceanic and Atmospheric Administration... Read more…

By Oliver Peckham

Japan’s AIST Benchmarks Intel Optane; Cites Benefit for HPC and AI

February 19, 2020

Last April Intel released its Optane Data Center Persistent Memory Module (DCPMM) – byte addressable nonvolatile memory – to increase main memory capacity a Read more…

By John Russell

UK Announces £1.2 Billion Weather and Climate Supercomputer

February 19, 2020

While the planet is heating up, so is the race for global leadership in weather and climate computing. In a bombshell announcement, the UK government revealed p Read more…

By Oliver Peckham

The Massive GPU Cloudburst Experiment Plays a Smaller, More Productive Encore

February 13, 2020

In November, researchers at the San Diego Supercomputer Center (SDSC) and the IceCube Particle Astrophysics Center (WIPAC) set out to break the internet – or Read more…

By Oliver Peckham

Eni to Retake Industry HPC Crown with Launch of HPC5

February 12, 2020

With the launch of its Dell-built HPC5 system, Italian energy company Eni regains its position atop the industrial supercomputing leaderboard. At 52-petaflops p Read more…

By Tiffany Trader

Trump Budget Proposal Again Slashes Science Spending

February 11, 2020

President Donald Trump’s FY2021 U.S. Budget, submitted to Congress this week, again slashes science spending. It’s a $4.8 trillion statement of priorities, Read more…

By John Russell

Policy: Republicans Eye Bigger Science Budgets; NSF Celebrates 70th, Names Idea Machine Winners

February 5, 2020

It’s a busy week for science policy. Yesterday, the National Science Foundation announced winners of its 2026 Idea Machine contest seeking directions for futu Read more…

By John Russell

Fujitsu A64FX Supercomputer to Be Deployed at Nagoya University This Summer

February 3, 2020

Japanese tech giant Fujitsu announced today that it will supply Nagoya University Information Technology Center with the first commercial supercomputer powered Read more…

By Tiffany Trader

Julia Programming’s Dramatic Rise in HPC and Elsewhere

January 14, 2020

Back in 2012 a paper by four computer scientists including Alan Edelman of MIT introduced Julia, A Fast Dynamic Language for Technical Computing. At the time, t Read more…

By John Russell

Cray, Fujitsu Both Bringing Fujitsu A64FX-based Supercomputers to Market in 2020

November 12, 2019

The number of top-tier HPC systems makers has shrunk due to a steady march of M&A activity, but there is increased diversity and choice of processing compon Read more…

By Tiffany Trader

SC19: IBM Changes Its HPC-AI Game Plan

November 25, 2019

It’s probably fair to say IBM is known for big bets. Summit supercomputer – a big win. Red Hat acquisition – looking like a big win. OpenPOWER and Power processors – jury’s out? At SC19, long-time IBMer Dave Turek sketched out a different kind of bet for Big Blue – a small ball strategy, if you’ll forgive the baseball analogy... Read more…

By John Russell

Intel Debuts New GPU – Ponte Vecchio – and Outlines Aspirations for oneAPI

November 17, 2019

Intel today revealed a few more details about its forthcoming Xe line of GPUs – the top SKU is named Ponte Vecchio and will be used in Aurora, the first plann Read more…

By John Russell

IBM Unveils Latest Achievements in AI Hardware

December 13, 2019

“The increased capabilities of contemporary AI models provide unprecedented recognition accuracy, but often at the expense of larger computational and energet Read more…

By Oliver Peckham

SC19: Welcome to Denver

November 17, 2019

A significant swath of the HPC community has come to Denver for SC19, which began today (Sunday) with a rich technical program. As is customary, the ribbon cutt Read more…

By Tiffany Trader

Fujitsu A64FX Supercomputer to Be Deployed at Nagoya University This Summer

February 3, 2020

Japanese tech giant Fujitsu announced today that it will supply Nagoya University Information Technology Center with the first commercial supercomputer powered Read more…

By Tiffany Trader

51,000 Cloud GPUs Converge to Power Neutrino Discovery at the South Pole

November 22, 2019

At the dead center of the South Pole, thousands of sensors spanning a cubic kilometer are buried thousands of meters beneath the ice. The sensors are part of Ic Read more…

By Oliver Peckham

Leading Solution Providers

SC 2019 Virtual Booth Video Tour

AMD
AMD
ASROCK RACK
ASROCK RACK
AWS
AWS
CEJN
CJEN
CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
IBM
IBM
MELLANOX
MELLANOX
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
SIX NINES IT
SIX NINES IT
VERNE GLOBAL
VERNE GLOBAL
WEKAIO
WEKAIO

Jensen Huang’s SC19 – Fast Cars, a Strong Arm, and Aiming for the Cloud(s)

November 20, 2019

We’ve come to expect Nvidia CEO Jensen Huang’s annual SC keynote to contain stunning graphics and lively bravado (with plenty of examples) in support of GPU Read more…

By John Russell

Top500: US Maintains Performance Lead; Arm Tops Green500

November 18, 2019

The 54th Top500, revealed today at SC19, is a familiar list: the U.S. Summit (ORNL) and Sierra (LLNL) machines, offering 148.6 and 94.6 petaflops respectively, Read more…

By Tiffany Trader

Azure Cloud First with AMD Epyc Rome Processors

November 6, 2019

At Ignite 2019 this week, Microsoft's Azure cloud team and AMD announced an expansion of their partnership that began in 2017 when Azure debuted Epyc-backed instances for storage workloads. The fourth-generation Azure D-series and E-series virtual machines previewed at the Rome launch in August are now generally available. Read more…

By Tiffany Trader

Intel’s New Hyderabad Design Center Targets Exascale Era Technologies

December 3, 2019

Intel's Raja Koduri was in India this week to help launch a new 300,000 square foot design and engineering center in Hyderabad, which will focus on advanced com Read more…

By Tiffany Trader

In Memoriam: Steve Tuecke, Globus Co-founder

November 4, 2019

HPCwire is deeply saddened to report that Steve Tuecke, longtime scientist at Argonne National Lab and University of Chicago, has passed away at age 52. Tuecke Read more…

By Tiffany Trader

IBM Debuts IC922 Power Server for AI Inferencing and Data Management

January 28, 2020

IBM today launched a Power9-based inference server – the IC922 – that features up to six Nvidia T4 GPUs, PCIe Gen 4 and OpenCAPI connectivity, and can accom Read more…

By John Russell

Cray Debuts ClusterStor E1000 Finishing Remake of Portfolio for ‘Exascale Era’

October 30, 2019

Cray, now owned by HPE, today introduced the ClusterStor E1000 storage platform, which leverages Cray software and mixes hard disk drives (HDD) and flash memory Read more…

By John Russell

D-Wave’s Path to 5000 Qubits; Google’s Quantum Supremacy Claim

September 24, 2019

On the heels of IBM’s quantum news last week come two more quantum items. D-Wave Systems today announced the name of its forthcoming 5000-qubit system, Advantage (yes the name choice isn’t serendipity), at its user conference being held this week in Newport, RI. Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This