The Internet of Workflow

Photo Taken from https://www.azoquantum.com/

The next big thing, Nicolas Dubé, VP and chief technologist for HPE’s HPC business unit, told the virtual audience at SFE21, is something that will connect HPC and (broadly) all of IT – into what Dubé calls The Internet of Workflows (IoW).

Taken from “What’s After Exascale? The Internet of Workflows Says HPE’s Nicolas Dubé“,

The IoW, said Dubé, is about “applying those principles to a much broader set of scientific fields because we’re convinced that is where this is going.”

Dubé presented here are six takeaway, briefly touching on recent relevant advances as well as a list of requirements for developing the IoW.

  1. First the Basics. The effort to achieve exascale and the needs of heterogeneous computing generally were catalysts in producing technologies needed for IoW. Dubé also noted the “countless silicon startups doing accelerators” to tackle diverse workloads. Still, lots more work is needed. Here’s snippet on MCM’s expected impact on memory.
  2. White Hats & Data Sovereignty. A key issue, currently not fully addressed, is data sovereignty. Dubé agrees it’s a critical challenge now and will be even more so in an IoW world. He didn’t offer specific technology or practice guidelines.
  3. New Runtimes for a Grand Vision. It’s one thing to dream of IoW; it’s another to build it. Effective parallel programming for diverse devices and the availability of reasonably performant runtime systems able to accommodate device diversity are all needed.
  4. Chasing Performance Portability…Still. Tight vertical software integration as promoted by some (pick your favorite target vendor) isn’t a good idea, argued Dubé. This isn’t a new controversy and maybe it’s a hard-stop roadblock for IoW. We’ll see. Dubé argues for openness and says HPE (Cray) is trying to make the Cray Programming Environment a good choice.
  5. A Combinatorial Explosion of Configurations”. Now there’s an interesting turn of phrase. The avalanche of new chips from old and newcomers is a blessing and curse. Creating systems to accommodate the new wealth of choices is likewise exciting but daunting and expensive. Dubé argues we need to find ways to cut the costs of silicon innovation and subsequent systems to help bring the IoW into being.
  6. Worldwide Data Hub? If one is going to set goals, they may as well be big ones. Creating an infrastructure with reasonable governance and practices to support an IoW is a big goal. Data is at the core of nearly everything, Dubé argued.

Intel Accelerates Process and Packaging Innovations

Taken from Youtube – Intel NewRoom

During the “Intel Accelerated” webcast, Intel’s technology leaders revealed one of the most detailed process and packaging technology roadmaps the company has provided. The event on July 26, 2021, showcased a series of foundational innovations that will power products through 2025 and beyond. As part of the presentations, Intel announced RibbonFET, its first new transistor architecture in more than a decade, and PowerVia, an industry-first new backside power delivery method. (Credit: Intel Corporation)

AMD strong comeback

In the article from the next platform “AMD is finally trusted in the Datacentre again

AMD turned in the best quarter that we can remember, and is now firmly in place as the gadfly counterbalance to the former hegemony of Intel. And that is good for everyone who buys a game console, a PC, an edge device, and a server. And the game is only going to get more interesting with Intel getting its chip together and preparing for a long battle with AMD and other XPU usurpers in chip design and as well as Taiwan Semiconductor Manufacturing Corp in chip etching and packaging.

We do get some hints, however. Lisa Su, AMD’s president and chief executive officer, said that AMD’s datacenter business – at this point meaning Epyc CPUs and Instinct GPU accelerators – comprised more than 20 percent of the company’s overall sales, and the big driver in this quarter was not just second generation “Rome” Epyc 7002 and third generation “Milan” Epyc 7003 server chips – Rome is still outselling Milan, but the crossover is coming in the third quarter of this year – but the Radeon Instinct M100 GPU accelerators launched last fall. The datacenter GPU business more than doubled from a year ago, according to Su, and AMD expects it to continue to grow in the second half of the year as the 1.5 exaflops “Frontier” supercomputer at Oak Ridge National Laboratory in the United States, the as-yet-unnamed pre-exascale system at Pawsey Supercomputing Center in Australia, and the Lumi pre-exascale system in Finland all get their Radeon Instinct motors installed.

the Next Platform “AMD is finally trusted in the Datacentre again”

rsync and write failed with No Space left on Device (28)

If you run an rsync such as this command

% rsync -lH -rva --no-inc-recursive --progress gromacs remote_server:/usr/local

and you encountered something like this

% rsync: write failed on "/usr/local": No space left on device (28)

After checking that the source and destination have sufficient space, you are still encountering the issue, you may want to put this parameter in “–inplace”. According to the rsync man page. “This option changes how rsync transfers a file when its data needs to be updated: instead of the default method of creating a new copy of the file and moving it into place when it is complete, rsync instead writes the updated data directly to the destination file.

WARNING: you should not use this option to update files that are being accessed by others, so be careful when choosing to use this for a copy. For more information, do take a look at https://download.samba.org/pub/rsync/rsync.html

% rsync -lH -rva --inplace --no-inc-recursive --progress gromacs remote_server:/usr/local

US and Japan join hands to counter China in Quantum Computing

The IBM Quantum System One is Japan’s first commercial quantum computer. (Photo by Hiroshi Endo)

IBM has unveiled Japan’s first quantum computer for commercial applications, its Japanese arm said Tuesday, as Washington and Tokyo join hands to push the field toward practical use with an eye on recent strides by China.

The IBM Quantum System One is up and running at the Kawasaki Business Incubation Center near Tokyo. The University of Tokyo will administer access to the machine, which will be used by the Quantum Innovation Initiative Consortium, whose members include Keio University and Toyota Motor. The project marks a step forward for Japan-U.S. cooperation in a fiercely competitive field that has become embroiled in the battle with China for technological superiority. Quantum computing was among the areas of cooperation discussed by Japanese Prime Minister Yoshihide Suga and U.S. President Joe Biden at their April summit.

Nikkei Asia “US and Japan counter China with powerful IBM quantum computer”

Full Article can be found at US and Japan counter China with powerful IBM quantum computer

Quantum Computing can revolutionize AI

Quantum computers can process complex information at a mind-boggling speed and should eventually vastly outperform even the most powerful of today’s conventional computers. This includes the rapid training of machine learning models and the creation of optimized algorithms. Years of analysis can be cut to a short time with an optimized and stable AI that is powered by quantum computing. The combined solution is expected to bring changes to the AI hardware ecosystem

Techhq.com “Why AI will be so core to real-world quantum computing”

In a report by McKinsey, quantum computers have four fundamental capabilities that differentiate them from today’s classical computers: quantum simulation, in which quantum computers model complex molecules; optimization (that is, solving multivariable problems with unprecedented speed); quantum artificial intelligence (AI), utilizes better algorithms that could transform machine learning across industries as diverse as pharma and automotive; and prime factorization, which could revolutionize encryption.

Techhq.com “Why AI will be so core to real-world quantum computing”

For more information, do take a look at Why AI will be so core to real-world quantum computing

Images Taken from https://sociable.co/technology/could-quantum-computing-and-exotic-materials-facilitate-ai-human-cyborgs/

Quick Fix to add Queue for PBS Pro

One of the quickest way to install the PBS Professional Queue is take 1 queue and modify the example

At your node holding the PBS Scheduler

# qmgr -c "print queue @default"
.....
.....
# Create and define queue q64
#
create queue q64
set queue q64 queue_type = Execution
set queue q64 Priority = 100
set queue q64 resources_max.ncpus = 256
set queue q64 resources_max.walltime = 500:00:00
set queue q64 resources_default.charge_rate = 0.04
set queue q64 default_chunk.Qlist = q64
set queue q64 max_run_res.ncpus = [u:PBS_GENERIC=256]
set queue q64 enabled = True
set queue q64 started = True
#
.....
.....

Copy out the information and pipe it into a file

# qmgr -c "print queue q64" > q64_new_queue

Edit the File and save it

# Create and define queue q64_new_queue
#
create queue q64_new_queue
#
set queue q64_new_queue queue_type = Execution
set queue q64_new_queue Priority = 100
set queue q64_new_queue resources_max.ncpus = 256
set queue q64_new_queue resources_max.walltime = 500:00:00
set queue q64_new_queue resources_default.charge_rate = 0.04
set queue q64_new_queue default_chunk.Qlist = q64
set queue q64_new_queue max_run_res.ncpus = [u:PBS_GENERIC=256]
set queue q64_new_queue enabled = True
set queue q64_new_queue started = True
#

Pipe it back to qmgr

# qmgr < q64_new_queue

You should be able to see the new queue

...
...

# Create and define queue q64_new_queue
#
create queue q64_new_queue
#
set queue q64_new_queue queue_type = Execution
set queue q64_new_queue Priority = 100
set queue q64_new_queue resources_max.ncpus = 256
set queue q64_new_queue resources_max.walltime = 500:00:00
set queue q64_new_queue resources_default.charge_rate = 0.04
set queue q64_new_queue default_chunk.Qlist = q64
set queue q64_new_queue max_run_res.ncpus = [u:PBS_GENERIC=256]
set queue q64_new_queue enabled = True
set queue q64_new_queue started = True
#
...
...

Install and Enable EPEL Repository for CentOS 7.x

The EPEL is an acronym for Extra Packages for Enterprise Linux. The EPEL repository used by the following Linux Distributions:

  • Red Hat Enterprise Linux (RHEL)
  • CentOS
  • Oracle Linux

On the Terminal,

Install EPEL Repository

# yum -y install epel-release

Refresh EPEL Repository

# yum repolist

Install Packages from EPEL Repository

# yum install -y htop

Search and install Package (E.g. htop)

# yum --disablerepo="*" --enablerepo="epel" list available | grep 'htop'

High Performance Computing is at Inflection Point

A group of researchers led by Martin Schulz of the Leibniz Supercomputing Center (Munich) presented a paper in which they argue HPC architectural landscape of High-Performance Computing (HPC) is undergoing a seismic shift.

The Full Article is taken from Summer Reading: “High-Performance Computing Is at an Inflection Point”

4 Guiding Principles for the Future of HPC Architecture

  • Energy consumption is no longer merely a cost factor but also a hard feasibility constraint for facilities.
  • Specialization is key to further increase performance despite stagnating frequencies and within limited energy bands.
  • A significant portion of the energy budget is spent moving data and future architectures must be designed to minimize such data movements.
  • Large-scale computing centers must provide optimal computing resources for increasingly differentiated workloads.

Ideas Snippets – Integrated Heterogeneity

Integrated Heterogenous Systems are a promising alternative, which integrate multiple specialized architectures on a single node while keeping the overall system architecture a homogeneous collection of mostly identical nodes. This allows applications to switch quickly between accelerator modules at a fine-grained scale, while minimizing the energy cost and performance overhead, enabling truly heterogeneous applications.

Integrated HPC Systems and How They will Change HPC System Operations
Leibniz-SC-Paper_fig1-768×449

Ideas Snippets – Challenges of a Integrated Heterogeneity

a single application is likely not going use all specialized compute elements at the same time, leading to idle processing elements. Therefore, the choice of the best-suited accelerator mix is an important design criterion during procurement, which can only be achieved via co-design between the computer center and its users on one side and the system vendor on the other. Further, at runtime, it will be important to dynamically schedule and power the respective compute resources. Using power overprovisioning, i.e., planning for a TDP and maximal node power that is reached with a subset of dynamically chosen accelerated processing elements, this can be easily achieved, but requires novel software approaches in system and resource management.”

They note the need for programming environments and abstractions to exploit the different on-node accelerators. “For widespread use, such support must be readily available and, in the best case, in a unified manner in one programming environment. OpenMP, with its architecture-agnostic target concept, is a good match for this. Domain-specific frameworks, as they are, e.g., common in AI, ML or HPDA (e.g., Tensorflow, Pytorch or Spark), will further help to hide this heterogeneity and help make integrated platforms accessible to a wide range of users

HPCWire – Summer Reading: “High-Performance Computing Is at an Inflection Point”

Idea Snippets – Coping with Idle Periods among different Devices (Project Regale)

Application Level. Changing application resources in terms of number and type of processing elements dynamically.

Node Level. Changing node settings, e.g. power/energy consumption via techniques like DVFS or power capping as well as node level partitioning of memory, caches, etc.

System Level. Adjusting system operation based on work- loads or external inputs, e.g., energy prices or supply levels.

HPCWire – Summer Reading: “High-Performance Computing Is at an Inflection Point”