Julia Programming’s Dramatic Rise in HPC and Elsewhere

By John Russell

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, the gold standard programming languages for fast performance on computationally intensive problems were C and Fortran – maybe they still are. Fast forward to 2020 and Julia is making a run at the top and Edelman won last year’s IEEE Sidney Fernbach Award presented at SC19 for, among other things, his work on Julia.

Consider recent stats on Julia adoption. By January 1, 2019, reports Julialang.org, the total downloads of Julia reached 7.3 million. That number jumped to 12.9 million, a 77 percent increase, by January 1, 2020. The number of published citations for same period rose 66 percent from 1048 to 1680. In his SC19 talk, Edelman noted that as of October 2019 there were 3,119 Julia packages available, up from 1,688 at the year’s start. Those numbers are impressive all around.

In September, Julia joined the ranks of computing languages that have achieved peak performance exceeding one petaflop per second – the so-called ‘Petaflop Club.’ The Julia application that achieved this milestone is called Celeste. The Celeste team developed a new parallel computing method to process the entire Sloan Digital Sky Survey dataset and loaded an aggregate of 178 terabytes of image data to produce the most accurate catalog of 188 million astronomical objects in just 14.6 minutes. Celeste achieved peak performance of 1.54 petaflops using 1.3 million threads on 9,300 Knights Landing (KNL) nodes of the Cori supercomputer at NERSC – a performance improvement of 1,000x in single-threaded execution.

Alan Edelman, MIT

You get the idea. Julia is on a roll. Whether Julia will challenge Python the way Python once challenged and then surpassed Java is an interesting question being bandied about. What’s clear is that after percolating along steadily during its early years, Julia use is growing quickly – much to Edelman’s delight.

The tension between the high performance delivered by so-called static programming languages and the lesser performance delivered by high-level programming languages, which emphasize abstraction, speed of development, and portability, hasn’t gone away, noted Edelman. But convenience with sufficient performance is winning out. Moreover, the rise of heterogeneous computing and the complications it presents to programmers has increased the tilt away from static programming.

In his engaging SC19 talk, Edelman noted:

“When you’re writing various algorithms, you don’t necessarily want to think about whether you’re on a GPU, or whether you’re on a distributed computer. You don’t necessarily want to think about how you’ve implemented the specific data structure. What you want to do is talk about what you want to compute, not how you want to compute it, right? That is the big problem, to get people to talk about what you want to compute, and not how you want to compute it. Because if you put in your software, how you’re going to compute it, and if your software is filled with that muck, I promise you, nobody’s ever going to change it. No one’s going to innovate on it. When the person who wrote it is no longer in the project, no one’s ever going to touch it.

“[S]ome of the reasons why Julia is working very well is because we have particularly well-designed abstractions. We have something called multiple dispatch and we have a very careful balance between the static and dynamic. It interfaces with LLVM. It plays nicely with Python. We also have had lots of people take legacy codes in MPI, and plug them into Julia – you don’t get all the benefits, but what you do have, which might be the most important benefit, is other people can now run your code once it’s inside of Julia. So it’s much easier for other people. You can actually give your old code new life when you plug it into a higher level language.”

Julia, say advocates, minimizes performance penalties because it was designed from the outset with parallel computing in mind and with making use of high-performing abstractions able to exploit the latest libraries and deliver portability. Edelman presented an example in which a group of researchers decided to scrap their legacy climate code in Fortran and write it from scratch in Julia. There was some discussion around performance tradeoffs they might encounter in the move to a high level programming language. The group was willing to accept a 3x slowdown for the flexibility of the language. Instead, said Edelman, the switch produced 3x speedup.

 

He briefly presented a second example in which Julia was used with GPUs and skirted CUDA.

“I’m going to go over really fast a little bit on how we do Julia on GPUs. Because we have these different levels of abstraction, we’re able to reason about what’s going on at various different levels. If you only have that very lowest level on a GPU again, you can roll up your sleeves and work really hard, but you don’t get any code reuse. We have the saying in the Julia world, where if you’ve copied and pasted code, and you just modified a few things, then you’ve done something wrong. We’re trying to eliminate the copying and pasting the code, not only by you, but somebody else in the community shouldn’t have to go and take somebody else’s code and copy and paste it. That shouldn’t be necessary. So there’s a lot going on in here (see slide below). But the main point is that it’s not just queued in Julia, but it’s actually Julia running on the GPUs. And so that’s, that’s pretty exciting.”

Edelman’s perspective on coding and mathematics is interesting. “You know, a lot of us get this impression from universities and from teaching that you learn some math and then you [build] an algorithm, and then you code it up as if there is the algorithm first, and then the coding is sort of the secondary. But you know, more and more now, the code is the math,” said Edelman. This idea, he suggests, should inform our thinking about coding generally; it’s yet another effective abstraction.

The video is best watched (or listened to) to get the breezy yet substantive flavor of Edelman’s ideas and Julia’s capabilities.

“Julia was always designed to be a high level of parallel computing language, even from day one. That’s what I wanted. This is the problem that I personally wanted to see solved. We’re not fully there yet. But Julia is a highlight. You could do distributed computing, you could do GPU computing, you could do shared memory computing. We have models, you know, asynchronous computing, whatever you’d like to do we have models to do it now. And the real question, the one that everybody asked, the one that none of us really knows how to do, the deep intellectual problem is how to put it all together. But if we all work together at it, if we actually all share code, and, you know, hammer away at it, I think we could actually solve this problem.”

Link to intro paper: https://arxiv.org/pdf/1209.5145.pdf

Link to Fernbach Award announcement: https://www.hpcwire.com/off-the-wire/julia-computing-chief-scientist-alan-edelman-wins-prestigious-ieee-sidney-fernbach-award/

Link to SC19 video: https://www.youtube.com/watch?v=nwdGsz4rc3Q

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!

Energy Exascale Earth System Model Version 2 Promises Twice the Speed

October 18, 2021

The Energy Exascale Earth System Model (E3SM) is an ongoing Department of Energy (DOE) earth system modeling, simulation and prediction project aiming to “assert and maintain an international scientific leadership posi Read more…

Intel Reorgs HPC Group, Creates Two ‘Super Compute’ Groups

October 15, 2021

Following on changes made in June that moved Intel’s HPC unit out of the Data Platform Group and into the newly created Accelerated Computing Systems and Graphics (AXG) business unit, led by Raja Koduri, Intel is making further updates to the HPC group and announcing... Read more…

Royalty-free stock illustration ID: 1938746143

MosaicML, Led by Naveen Rao, Comes Out of Stealth Aiming to Ease Model Training

October 15, 2021

With more and more enterprises turning to AI for a myriad of tasks, companies quickly find out that training AI models is expensive, difficult and time-consuming. Finding a new approach to deal with those cascading challenges is the aim of a new startup, MosaicML, that just came out of stealth... Read more…

NSF Awards $11M to SDSC, MIT and Univ. of Oregon to Secure the Internet

October 14, 2021

From a security standpoint, the internet is a problem. The infrastructure developed decades ago has cracked, leaked and been patched up innumerable times, leaving vulnerabilities that are difficult to address due to cost Read more…

SC21 Announces Science and Beyond Plenary: the Intersection of Ethics and HPC

October 13, 2021

The Intersection of Ethics and HPC will be the guiding topic of SC21's Science & Beyond plenary, inspired by the event tagline of the same name. The evening event will be moderated by Daniel Reed with panelists Crist Read more…

AWS Solution Channel

Cost optimizing Ansys LS-Dyna on AWS

Organizations migrate their high performance computing (HPC) workloads from on-premises infrastructure to Amazon Web Services (AWS) for advantages such as high availability, elastic capacity, latest processors, storage, and networking technologies; Read more…

Quantum Workforce – NSTC Report Highlights Need for International Talent

October 13, 2021

Attracting and training the needed quantum workforce to fuel the ongoing quantum information sciences (QIS) revolution is a hot topic these days. Last week, the U.S. National Science and Technology Council issued a report – The Role of International Talent in Quantum Information Science... Read more…

Intel Reorgs HPC Group, Creates Two ‘Super Compute’ Groups

October 15, 2021

Following on changes made in June that moved Intel’s HPC unit out of the Data Platform Group and into the newly created Accelerated Computing Systems and Graphics (AXG) business unit, led by Raja Koduri, Intel is making further updates to the HPC group and announcing... Read more…

Royalty-free stock illustration ID: 1938746143

MosaicML, Led by Naveen Rao, Comes Out of Stealth Aiming to Ease Model Training

October 15, 2021

With more and more enterprises turning to AI for a myriad of tasks, companies quickly find out that training AI models is expensive, difficult and time-consuming. Finding a new approach to deal with those cascading challenges is the aim of a new startup, MosaicML, that just came out of stealth... Read more…

Quantum Workforce – NSTC Report Highlights Need for International Talent

October 13, 2021

Attracting and training the needed quantum workforce to fuel the ongoing quantum information sciences (QIS) revolution is a hot topic these days. Last week, the U.S. National Science and Technology Council issued a report – The Role of International Talent in Quantum Information Science... Read more…

Eni Returns to HPE for ‘HPC4’ Refresh via GreenLake

October 13, 2021

Italian energy company Eni is upgrading its HPC4 system with new gear from HPE that will be installed in Eni’s Green Data Center in Ferrera Erbognone (a provi Read more…

The Blueprint for the National Strategic Computing Reserve

October 12, 2021

Over the last year, the HPC community has been buzzing with the possibility of a National Strategic Computing Reserve (NSCR). An in-utero brainchild of the COVID-19 High-Performance Computing Consortium, an NSCR would serve as a Merchant Marine for urgent computing... Read more…

UCLA Researchers Report Largest Chiplet Design and Early Prototyping

October 12, 2021

What’s the best path forward for large-scale chip/system integration? Good question. Cerebras has set a high bar with its wafer scale engine 2 (WSE-2); it has 2.6 trillion transistors, including 850,000 cores, and was fabricated using TSMC’s 7nm process on a roughly 8” x 8” silicon footprint. Read more…

What’s Next for EuroHPC: an Interview with EuroHPC Exec. Dir. Anders Dam Jensen

October 7, 2021

One year after taking the post as executive director of the EuroHPC JU, Anders Dam Jensen reviews the project's accomplishments and details what's ahead as EuroHPC's operating period has now been extended out to the year 2027. Read more…

University of Bath Unveils Janus, an Azure-Based Cloud HPC Environment

October 6, 2021

The University of Bath is upgrading its HPC infrastructure, which it says “supports a growing and wide range of research activities across the University.” Read more…

Ahead of ‘Dojo,’ Tesla Reveals Its Massive Precursor Supercomputer

June 22, 2021

In spring 2019, Tesla made cryptic reference to a project called Dojo, a “super-powerful training computer” for video data processing. Then, in summer 2020, Tesla CEO Elon Musk tweeted: “Tesla is developing a [neural network] training computer... Read more…

Enter Dojo: Tesla Reveals Design for Modular Supercomputer & D1 Chip

August 20, 2021

Two months ago, Tesla revealed a massive GPU cluster that it said was “roughly the number five supercomputer in the world,” and which was just a precursor to Tesla’s real supercomputing moonshot: the long-rumored, little-detailed Dojo system. Read more…

Esperanto, Silicon in Hand, Champions the Efficiency of Its 1,092-Core RISC-V Chip

August 27, 2021

Esperanto Technologies made waves last December when it announced ET-SoC-1, a new RISC-V-based chip aimed at machine learning that packed nearly 1,100 cores onto a package small enough to fit six times over on a single PCIe card. Now, Esperanto is back, silicon in-hand and taking aim... Read more…

CentOS Replacement Rocky Linux Is Now in GA and Under Independent Control

June 21, 2021

The Rocky Enterprise Software Foundation (RESF) is announcing the general availability of Rocky Linux, release 8.4, designed as a drop-in replacement for the soon-to-be discontinued CentOS. The GA release is launching six-and-a-half months... Read more…

US Closes in on Exascale: Frontier Installation Is Underway

September 29, 2021

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, held by Zoom this week (Sept. 29-30), it was revealed that the Frontier supercomputer is currently being installed at Oak Ridge National Laboratory in Oak Ridge, Tenn. The staff at the Oak Ridge Leadership... Read more…

Intel Completes LLVM Adoption; Will End Updates to Classic C/C++ Compilers in Future

August 10, 2021

Intel reported in a blog this week that its adoption of the open source LLVM architecture for Intel’s C/C++ compiler is complete. The transition is part of In Read more…

Intel Reorgs HPC Group, Creates Two ‘Super Compute’ Groups

October 15, 2021

Following on changes made in June that moved Intel’s HPC unit out of the Data Platform Group and into the newly created Accelerated Computing Systems and Graphics (AXG) business unit, led by Raja Koduri, Intel is making further updates to the HPC group and announcing... Read more…

Hot Chips: Here Come the DPUs and IPUs from Arm, Nvidia and Intel

August 25, 2021

The emergence of data processing units (DPU) and infrastructure processing units (IPU) as potentially important pieces in cloud and datacenter architectures was Read more…

Leading Solution Providers

Contributors

AMD-Xilinx Deal Gains UK, EU Approvals — China’s Decision Still Pending

July 1, 2021

AMD’s planned acquisition of FPGA maker Xilinx is now in the hands of Chinese regulators after needed antitrust approvals for the $35 billion deal were receiv Read more…

HPE Wins $2B GreenLake HPC-as-a-Service Deal with NSA

September 1, 2021

In the heated, oft-contentious, government IT space, HPE has won a massive $2 billion contract to provide HPC and AI services to the United States’ National Security Agency (NSA). Following on the heels of the now-canceled $10 billion JEDI contract (reissued as JWCC) and a $10 billion... Read more…

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

Quantum Roundup: IBM, Rigetti, Phasecraft, Oxford QC, China, and More

July 13, 2021

IBM yesterday announced a proof for a quantum ML algorithm. A week ago, it unveiled a new topology for its quantum processors. Last Friday, the Technical Univer Read more…

The Latest MLPerf Inference Results: Nvidia GPUs Hold Sway but Here Come CPUs and Intel

September 22, 2021

The latest round of MLPerf inference benchmark (v 1.1) results was released today and Nvidia again dominated, sweeping the top spots in the closed (apples-to-ap Read more…

Frontier to Meet 20MW Exascale Power Target Set by DARPA in 2008

July 14, 2021

After more than a decade of planning, the United States’ first exascale computer, Frontier, is set to arrive at Oak Ridge National Laboratory (ORNL) later this year. Crossing this “1,000x” horizon required overcoming four major challenges: power demand, reliability, extreme parallelism and data movement. Read more…

Intel Unveils New Node Names; Sapphire Rapids Is Now an ‘Intel 7’ CPU

July 27, 2021

What's a preeminent chip company to do when its process node technology lags the competition by (roughly) one generation, but outmoded naming conventions make i Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire