Storage IO straight to GPU

The parallel processing power of the GPU (Graphics Processing Unit) cannot be denied. One year ago, nVidia® overtook Intel® in market capitalization. And today, they have doubled their market cap lead over Intel®,  [as of July 2, 2021] USD$510.53 billion vs USD$229.19 billion.

Thus it is not surprising that storage architectures are changing from the CPU-centric paradigm to take advantage of the burgeoning prowess of the GPU. And 2 announcements in the storage news in recent weeks have caught my attention – Windows 11 DirectStorage API and nVidia® Magnum IO GPUDirect® Storage.

nVidia GPU

Exciting the gamers

The Windows DirectStorage API feature is only available in Windows 11. It was announced as part of the Xbox® Velocity Architecture last year to take advantage of the high I/O capability of modern day NVMe SSDs. DirectStorage-enabled applications and games have several technologies such as D3D Direct3D decompression/compression algorithm designed for the GPU, and SFS Sampler Feedback Streaming that uses the previous rendered frame results to decide which higher resolution texture frames to be loaded into memory of the GPU and rendered for the real-time gaming experience.

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Thinking small to solve Big

[This article was posted in my LinkedIn at https://www.linkedin.com/pulse/thinking-small-solve-big-chin-fah-heoh/ on Sep 9th 2019]

The world’s economy has certainly turned. And organizations, especially the SMEs, are demanding more. There were times that many technology vendors and their tier 1 systems integrators could get away with plenty of high level hobnobbing, and showering the prospect with their marketing wow-factor. But those fancy, smancy days are drying up and SMEs now do a lot of research and demand a more elaborate and a more comprehensive technology solution to their requirements.

The SMEs have the same problems faced by the larger organizations. They want more data stored, protected and recoverable, and maximize the value of data. However, their risk factors are much higher than the larger enterprises, because a disruption or a simple breakdown could affect their business and operations far greater than larger organizations. In most situations, they have no safety net.

So, the past 3 odd years, I have learned that as a technology solution provider, as a systems integrator to SMEs, I have to be on-the-ball with their pains all the time. And I have to always remember that they do not have the deep pockets, especially when the economy in Malaysia has been soft for years.

That is why I have gravitated to technology solutions that matter to the SMEs and gentle to their pockets as well. Take for instance a small company called Itxotic I discovered earlier this year. Itxotic is a 100% Malaysian home-grown technology startup, focusing on customized industry intelligence, notably computer vision AI. Their prominent technology include defect detection in a manufacturing production line.

 

At the Enterprise level, it is easy for large technology providers like Hitachi or GE or Siemens to peddle similar high-tech solutions to SMEs requirements. But this would come with a price tag of hundreds of thousands of ringgit. SMEs will balk at such a large investment because the price tag is definitely something not comprehensible to the SME factories. That is why I gravitated to the small thinking of Itxotic, where their small, yet powerful technology solves big problems in the SMEs.

And this came about when more Industry 4.0 opportunities started to come into my radar. Similarly, I was also approached to look into a edge-network data analytics technology to be integrated into PLCs (programmable logic controllers). At present, the industry consultants who invited me, are peddling a foreign technology solution, and the technology costs RM13,000 per CPU core. In a typical 4-core processor IPC (industrial PC), that is a whopping RM52,000, minus the hardware and integration services. This can easily drive up the selling price of over RM100K, again, a price tag that will trigger a mini heart attack with the SMEs.

I am tasked by the industry consultants to design a more cost-friendly, aka cheaper solution and today, we are already building an alternative with Apache Kafka, its connectors and Grafana for visual reporting. And I think the cost to build this alternative technology will be probably 70-80% cheaper than the one they are reselling now. The “think small, solve Big” mantra is beginning to take hold, and I am excited about it.

In the “small” mantra, I mean to be intimate and humble with the end users. One lesson I have learned over the past years is, the SMEs count on their technology partners to be with them. They have no room for failure because a costly failure is likely to be devastating to their operations and business. Know the technology you are pitching well, so that the SMEs are confident that you can deliver, not some over-the-top high-level technology pitch. Look deep into the technology integration with their existing technology and operations, and carefully and meticulously craft and curate a well mapped plan for them. Commit to their journey to ensure their success.

I have often seen technology vendors and resellers leaving SMEs high and dry when it comes to something outside their scope, and this has been painful. That is why this isn’t a downgrade for me when I started working with the SMEs more often in the past 3 years, even though I have served the enterprise for more than 25 years. This invaluable lesson is an upgrade for me to serve my SME customers better.

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Storage Performance Considerations for AI Data Paths

The hype of Deep Learning (DL), Machine Learning (ML) and Artificial Intelligence (AI) has reached an unprecedented frenzy. Every infrastructure vendor from servers, to networking, to storage has a word to say or play about DL/ML/AI. This prompted me to explore this hyped ecosystem from a storage perspective, notably from a storage performance requirement point-of-view.

One question on my mind

There are plenty of questions on my mind. One stood out and that is related to storage performance requirements.

Reading and learning from one storage technology vendor to another, the context of everyone’s play against their competitors seems to be  “They are archaic, they are legacy. Our architecture is built from ground up, modern, NVMe-enabled“. And there are more juxtaposing, but you get the picture – “We are better, no doubt“.

Are the data patterns and behaviours of AI different? How do they affect the storage design as the data moves through the workflow, the data paths and the lifecycle of the AI ecosystem?

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Whither HPC, HPE?

HPE is acquiring Cray Inc. Almost 3 years ago, HPE acquired SGI. Back in 2017, HPE partnered WekaIO, and invested big in the latest Series C funding of WekaIO just weeks ago.

Cray, SGI and WekaIO are all strong HPC technology companies. Given the strong uptick in the HPC market, especially commercial HPC, we cannot deny HPE’s ambition to become the top SuperComputing and HPC vendor in the industry. Continue reading

Connecting ideas and people with Dell Influencers

[Disclosure: I was invited by Dell Technologies as a delegate to their Dell Technologies World 2019 Conference from Apr 29-May 1, 2019 in the Las Vegas USA. My expenses, travel, accommodation and conference fees were covered by Dell Technologies, the organizer and I was not obligated to blog or promote their technologies presented at this event. The content of this blog is of my own opinions and views]

I just got home from Vegas yesterday after attending my 2nd Dell Technologies World as one of the Dell Luminaries. The conference was definitely a bigger one than the one last year, with more than 15,000 attendees. And there was a frenzy of announcements, from Dell Technologies Cloud to new infrastructure solutions, and more. The big one for me, obviously was Azure VMware Solutions officiated by Microsoft CEO Satya Nadella and VMware CEO Pat Gelsinger, with Michael Dell bringing together the union. I blogged about Dell jumping into the cloud in a big way.

AI Tweetup

In the razzmatazz, the most memorable moments were one of the Tweetups organized by Dr. Konstanze Alex (Konnie) and her team, and Tech Field Day Extra.

Tweetup was alien to me. I didn’t know how the concept work and I did google tweetup before that. There were a few tweetups on the topics of data protection and 5G, but the one that stood out for me was the AI tweetup.

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Is AI my friend?

I am sorry, Dave …

Let’s start this story with 2 supposed friends – Dave and Hal.

How do we become friends?

We have friends and we have enemies. We become friends when trust is established. Trust is established when there is an unsaid pact, a silent agreement that I can rely on you to keep my secrets private. I will know full well that you will protect my personal details with a strong conviction. Your decisions and your actions towards me are in my best interest, unbiased and would benefit both me and you.

I feel secure with you.

AI is my friend

When the walls of uncertainty and falsehood are broken down, we trust our friends more and more. We share deeper secrets with our friends when we believe that our privacy and safety are safeguarded and protected. We know well that we can rely on them and their decisions and actions on us are reliable and unbiased.

AI, can I count on you to protect my privacy and give me security that my personal data is not abused in the hands of the privileged few?

AI, can I rely on you to be ethical, unbiased and give me the confidence that your decisions and actions are for the benefit and the good of me, myself and I?

My AI friends (maybe)

As I have said before, I am not a skeptic. When there is plenty of relevant, unbiased data fed into the algorithms of AI, the decisions are fair. People accept these AI decisions when the degree of accuracy is very close to the Truth. The higher the accuracy, the greater the Truth. The greater the Truth, the more confident people are towards the AI system.

Here are some AI “friends” in the news:

But we have to careful here as well. Accuracy can be subjective, paradoxical and enigmatic. When ethics are violated, we terminate the friendship and we reject the “friend”. We categorically label him or her as an enemy. We constantly have to check, just like we might, once in a while, investigate on our friends too.

In Conclusion

AI, can we be friends now?

[Apology: sorry about the Cyberdyne link 😉 ]

[This blog was posted in LinkedIn on Apr 19th 2019]

We got to keep more data

Guess which airport has won the most awards in the annual Skytrax list? Guess which airport won 480 awards since its opening in 1981? Guess how this airport did it?

Data Analytics gives the competive edge.

Serving and servicing more than 65 million passengers and travellers in 2018, and growing, Changi Airport Singapore sets a very high level customer service. And it does it with the help of technology, something they call Smart (Service Management through Analytics and Resource Transformation) Airport. In an ultra competitive and cut-throat airline business, the deep integration of customer-centric services and the ultimate traveller’s experience are crucial to the survival and growth of airlines. And it has definitely helped Singapore Airlines to be the world’s best airlines in 2018, its 4th win.

To achieve that, Changi Airport relies on technology and lots of relevant data for deep insights on how to serve its customers better. The details are well described in this old news article.

Keep More Relevant Data for Greater Insights

When I mean more data, I do not mean every single piece of data. Data has to be relevant to be useful.

How do we get more insights? How can we teach systems to learn? How to we develop artificial intelligence systems? By having more relevant data feeding into data analytics systems, machine learning and such.

As such, a simple framework for building from the data ingestion, to data repositories to outcomes such as artificial intelligence, predictive and recommendations systems, automation and new data insights isn’t difficult to understand. The diagram below is a high level overview of what I work with most of the time. Continue reading

Malaysia, when will you take data privacy seriously?

It is sad. I get about 5-10 silly calls a week and a bunch of nonsense messages in my WhatsApp text and SMS. They waste my time, and it has been going on for years. Even worse is that my private details are out there, exposed and likely be abused too.

Once I got a call from a municipal attorney in the state of Kelantan that I have unpaid summons of several thousand ringgit. They have phone number, my IC number and they threatened to send me a note to arrest me if I didn’t pay up. The thing is, I have never been to Kelantan and I challenged them to send the attorney letter to my home address. The guy on the phone hung up.

In this age where digital information is there at our finger tips, the private details of victims are out there, easily used for unsavoury gains. And we as Malaysians should not shrug our shoulders and not assume that everything is like that, as if it is a Malaysia way of life. That apathy, our state of indifference, should be wiped out from our attitude. We should question the government, the agencies of why is our privacy not protected?

We have the Personal Data Protection Act, ratified in 2010. I don’t know the details of the act, but in its most basic form, don’t you think our private details should at least be protected from the telemarketers calling us selling their personal loans, time share travel suites, private massage (with benefits?) and other silly stuff? How can an act, as a law, be so toothless? Why bother drafting the act, and going through multiple iterations, I would suppose, and making it a law, and yet remain so unworthy to be called a act? Continue reading

Sexy HPC storage is all the rage

HPC is sexy

There is no denying it. HPC is sexy. HPC Storage is just as sexy.

Looking at the latest buzz from Super Computing Conference 2018 which happened in Dallas 2 weeks ago, the number of storage related vendors participating was staggering. Panasas, Weka.io, Excelero, BeeGFS, are the ones that I know because I got friends posting their highlights. Then there are the perennial vendors like IBM, Dell, HPE, NetApp, Huawei, Supermicro, and so many more. A quick check on the SC18 website showed that there were 391 exhibitors on the floor.

And this is driven by the unrelentless demand for higher and higher performance of computing, and along with it, the demands for faster and faster storage performance. Commercialization of Artificial Intelligence (AI), Deep Learning (DL) and newer applications and workloads together with the traditional HPC workloads are driving these ever increasing requirements. However, most enterprise storage platforms were not designed to meet the demands of these new generation of applications and workloads, as many have been led to believe. Why so?

I had a couple of conversations with a few well known vendors around the topic of HPC Storage. And several responses thrown back were to put Flash and NVMe to solve the high demands of HPC storage performance. In my mind, these responses were too trivial, too irresponsible. So I wanted to write this blog to share my views on HPC storage, and not just about its performance.

The HPC lines are blurring

I picked up this video (below) a few days ago. It was insideHPC Rich Brueckner interview with Dr. Goh Eng Lim, HPE CTO and renowned HPC expert about the convergence of both traditional and commercial HPC applications and workloads.

I liked the conversation in the video because it addressed the 2 different approaches. And I welcomed Dr. Goh’s invitation to the Commercial HPC community to work with the Traditional HPC vendors to help push the envelope towards Exascale SuperComputing.

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