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Lisa Su waited until the tail end of her speech last night to pull a literal behemoth out of her bag of tricks with the introduction of the Instinct MI300, a new high performance processor that blends advanced CPU and GPU technology towards maximum benefit for AI and HPC workloads. It’s not surprising to see AMD deliver another performance best. They’ve been on quite a roll for years most recently with the addition of their performance leading 4th generation EPYC processors late last year. What caught my eye about the introduction of the MI300 was the elegance of its design and what it foretells for the entire semiconductor arena moving forward. Let’s break it down.

Chiplet architecture wins the day

The MI300 is, per AMD’s claim, the world’s first chiplet based processor combining CPU and GPU cores. This is important for high performance computing as a combination of CPU and GPU can best support the demands of HPC and AI workloads. AMD has pulled this feat off through 3D stacking of nine 5nm chiplets sitting atop four 6nm chiplets and surrounded by a breathtaking 128GB of HBM3 memory. What we are seeing is modern silicon innovation tapping different silicon architectures tightly coupled with high performance memory and I/O reducing both compute latency and platform overhead, and it’s a harbinger of where the entire silicon ecosystem is aiming for future products.

The performance claimed by AMD is eye-opening. 8X the performance and 5X the perf/efficiency of the MI250, the nifty processor that fuels the AMD based Exascale class supercomputer at Oakridge National Lab. As Dr. Su held the chip aloft you could see that as a microprocessor architect herself she well understood what she’s delivered to the market and the importance to the trajectory of silicon innovation, and with that initial chip reveal the team at AMD should be proud.

Super-sized silo designs

But some questions come to mind. When will we see others jump into this APU/XPU pool? Intel shared more details of its upcoming Falcon Shores product at SC’22 which will feature a combination of Intel Xeon CPU and Intel Data Center GPU Max Series and is hinted to hit the market in 2024, behind anticipated MI300 launch in 2H'23. NVIDIA is also hard at work innovating what must be one of the best named products in the industry with its Grace Hopper superchip, again combining ARM CPU and GPU into a single package met with a proprietary 900 GB per second coherent interface.

As you look at this landscape it doesn’t take too long to realize that while these super-sized value meal chips will disrupt the market, some customers will want more control of exactly what chiplets they use. Enter UCIe, the new industry standard that will provide a common interconnect for chiplet designs which could open the door for a mixed architecture implementation. This is the reason I called UCIe one of the biggest disruptions on the compute landscape in an earlier blog. My mind also goes to the importance of foundry services in an era of multi-vendor chiplet designs as well as the emerging RISC-V architecture open-sourcing logic in a way we’ve never seen. Watch this space for more updates on all of these topics in 2023. For now, we’ll all need to wait as the MI300 and other supersized processors are readied for market. As always, thanks for engaging - Allyson

When you think of Oracle you don’t often think of scrappy disruptor. However, if you’ve been reading Oracle’s recent headlines you’ll uncover a company in transformation, shedding its skin as a traditionally minded enterprise software supplier to a cloud first services mindset. Along the way, OCI has gained major momentum with enterprise customers as the company leans in on a core differentiator – intimate understanding of enterprise customers.

I’ve been intrigued to see this story of mature player as disruptor play out, and I was excited with the chance to talk to Bev Crair, Senior VP of Oracle Cloud Infrastructure Compute, about how her team has architected its cloud to deliver differentiated value to its customers. Bev has a history of leadership across the industry most recently at Lenovo and Intel and has a reputation for driving high performance teams to deliver breakthroughs under her watch. What she described in our talk was a maniacal focus on delivering what, and only what, the customer requires. This seems simple but is awfully difficult to do within the world of automated re-provisioning of infrastructure to stand up customer services. More on the complexity of automation can be found in my talk with Abby Kearns. However, Oracle is doing just that and making it simple for customers to choose their services as part of a multi-cloud strategy.

Does this matter? Earlier I wrote about Couture Silicon for the Cloud, and Ampere’s delivery of processors devoid of instructional overhead of x86 alternatives. More plainly, Ampere is designing chips solely for the cloud so don’t need to think about capabilities that would be used in other designs like laptops or edge applications. This creates efficiency of design that is then passed on to the customer in terms of value. The chips fit like a glove for cloud workloads…or like a custom-tailored shirt if you extend the metaphor. Oracle’s promise to customers is similar. They’re delivering exactly the processor, memory and I/O configuration desired vs. finding closest proximity recipes found with the rest of the major cloud providers. And while many off the rack alternatives will do a great job delivering the performance required for the workload, there’s likely cost overhead that could otherwise be avoided.

Check out the interview to learn more about OCI innovation including their approach to multi-cloud and vendor partnerships delivering a rich selection of service offerings. And watch this space for more information about cloud service innovation. As always, thanks for engaging - Allyson

TechArena host Allyson Klein interview’s Senior Vice President of Oracle Cloud Infrastructure Compute Bev Crair about how OCI has delivered disruptive cloud services and simplified multi-cloud opportunity.

TechArena host Allyson Klein chats with Checkpoint Software's TJ Gonen about the state of cloud security and how security solutions must start with a developer lens

TechArena host Allyson Klein chats with Cloudflare infrastructure VP and Open Compute Board Chair Rebecca Weekly about the rising demands on cloud infrastructure across performance, design modularity, and sustainability.

Dear friends, It was time to confront the existential question on my mind for the last week. Have I been replaced by AI with the advent of ChatGPT? Will content forevermore be produced by machines, or does the turn of a phrase and unique and funny perspective still matter?

Let’s Get Ready to Rumble

To test my question, I decided to put ChatGPT to the task of writing a blog post on a topic I’ve been working on: the rise of complexity of cloud computing infrastructure and oversight. To add to the challenge, I wanted to include my two most recent guests on the TechArena to the writing assignment. I typed the following query…and waited approximately 45 seconds for the blog to be output. “Write a blog about cloud computing complexity and mention Rebecca Weekly and Abby Kearns”.

Read it…and Weep?

Here is ChatGPT’s view on cloud complexity with shout outs to Rebecca and Abby.

Cloud computing is a rapidly evolving field that has transformed the way we think about and use technology. While the benefits of cloud computing are numerous, it has also introduced a new level of complexity to the world of technology.

One of the key figures in the world of cloud computing is Rebecca Weekly, who is widely regarded as one of the foremost experts on the subject. She has written extensively about the complexity of cloud computing and the challenges it presents.

Weekly points out that the sheer scale of cloud computing systems can make them difficult to manage. These systems often consist of thousands of servers and other hardware components, all of which must be carefully configured and maintained in order to function properly. This can be a daunting task, even for experienced IT professionals.

Another source of complexity in cloud computing is the sheer number of different technologies and platforms that are involved. Cloud computing systems often use a wide range of different technologies, from virtualization software to data storage systems and more. This can make it difficult for IT professionals to keep up with the latest developments and ensure that their systems are running smoothly.

Abby Kearns, who is the executive director of the Cloud Foundry Foundation, has also spoken about the complexity of cloud computing. In a recent interview, Kearns noted that the complexity of cloud computing systems can be overwhelming, and that it is important for organizations to have a clear understanding of their specific needs in order to make the most of these systems.

Despite the challenges, however, the complexity of cloud computing systems is also a source of opportunity. As IT professionals continue to develop new tools and technologies to manage these systems, they are also creating new opportunities for businesses and organizations to take advantage of the power of the cloud.

In conclusion, while cloud computing has introduced a new level of complexity to the world of technology, it has also opened up new possibilities and opportunities. With the right tools and expertise, organizations can harness the power of the cloud to drive innovation and growth.

My Take

Well, I’d love to hear your perspective, but I don’t see this as a replacement for humans just quite yet. Is it a stunning first draft tool for people with writers block? Could be…a bail out students at mid-terms? Definitely. But at least with this first test I see a lack of, well, point of view which makes sense given the author. But of course, I didn’t have the courage to add “from my voice” to the prompt. More on that next time! As always, thanks for engaging - Allyson

TechArena host Allyson Klein chats with cloud innovator Abby Kearns about the state of cloud automation and how further advancement is required to keep apace of growing cloud complexity

More than a decade ago I worked on a team at Intel that introduced a vision for the future of cloud based on concepts of federation and automation. The goal was to build the cloud as a self-aware infrastructure where services were automatically provisioned and the cloud itself would monitor and re-balance resources based on workload usage. A colleague later coined this as a data center that thinks for itself.

As technology has progressed, we have made fantastic strides in delivering the core capabilities for this vision. Cloud native computing with the workload portability required for re-provisioning. Underlyling infrastructure that has flexible performance capabilities to manage different workload types, and the promise of infrastructure composability on the horizon. And stack automation giving us the ability to manage orchestration by policy. AI promises even more advancements towards that data center that can actually think through decisions historically managed by humans.

So why haven’t we achieved this nirvana? You could argue that the cloud itself has begat the core issue. Its very nature has made it incredibly easy to spin up workloads, different types of workloads (serverless, microservices etc) and this complexity has given rise to a equally complex set of tools to oversee more complex allocation of resourcing. I got a chance to talk to Abby Kearns, a leading innovator in cloud computing about the challenge. Abby is a powerhouse when it comes to deeply understand cloud stacks. As the former CTO of Puppet, she led the app stack automation company’s delivery of technology that helped inspire broad industry innovation in the space. Her viewpoints are also shaped by her time leading the Cloud Foundry, a powerful cloud consortium.

In our discussion, Abby pointed to this complexity as a key challenge that gates IT oversight today and offers some hope on cloud stack innovation. Check out the interview and as always thanks for engaging - Allyson

The last few weeks have been rich with new technology announcements, some with a lot of fanfare and others that happened in the corners of the tech arena that will grow in importance next year. Three grabbed my attention as topics that should squarely fit on your radar as tech innovations that will disproportionally reshape technology as we know it. Let’s take a look.

The new Google? OpenAI introduces ChatGPT (version 3.5)

We have all interacted with chat bots, and to interact with chat bots is to sometimes be infuriated by them. The technology simply has not advanced enough to mimic human thought, asking follow up questions, delivering detailed answers, and because of that we often find ourselves caught in a loop of a very predictable data decision tree that doesn’t deliver. I love Alexa, but she still can’t answer what the most important news of the day is, summarize abstract thoughts, or suggest ideas other than to place items in my Amazon shopping cart. I’m seeking a deeper relationship that at this point is very much one way.

Enter ChatGPT from the OpenAI team. This new AI model feels like it may be finally delivering on what we have been seeking all along…and more. Human-like communication that can deliver detailed answers, seek follow-up, and admit mistakes. This will be a step forward for consumer facing applications, but there’s more to the story. ChatGPT has shown promise to code software, write prose in the fashion of a specific author, and orchestrate cloud instances. The breadth of application is inspiring as the community starts integrating this technology into development streams, and the acute developer interest suggests that this will happen quickly. That doesn’t mean that there won’t be bumps in the road. Stack Overflow almost immediately suspended ChatGPT due to challenges with incorrect information in queries overwhelming the site. Others have called out that ChatGPT lacks morals, doesn’t necessarily like humans, and has an equal ability to do things like create phishing scams and Malware as  software for good intentions. More alarmist views express that it will re-define our markets and eliminate endless jobs, which certainly could be the case with this and other AI technology long term but likely won’t happen in week one of implementation.

The net takeaway? This is a powerful tool and integration into business could provide incredible advancement making it a technology and a space with expected future innovation not to be ignored.

Meta’s new Protein-Folding AI will Re-Shape Life

OK, maybe that sub-head was a bit hyperbolic, but Meta’s introduction of the ESM Metagenomic Atlas is an important follow on from DeepMind’s 2020 announcement of AlphaFold2 in massively accelerating protein shape predictions at the molecular level. First discussed on the TechArena by VAST Data’s Jeff Denworth, AlphaFold2 has had an incredible impact on the scientific community. Institutions like the Max Plank Institute have already come out stating that these tools have solved protein structure challenges that traditional science was failing to unlock, and Amazon made a splash earlier this year with the introduction of AWS Batch providing the computing power at scale to fuel research.

What’s the impact? Researchers can apply this to understand the human genome at a level that has been out of reach accelerating treatments for disease, new vaccinations and other medical breakthroughs. The Metagenomic Atlas has already mapped over 600 million proteins in its database driving National Geographic to name it as one of the top 22 innovations in 2022. Science magazine had already named AlphaFold2 and other AI driven research in this space as 2021’s breakthrough of the year.

The dystopian thinkers will connect the dots that all of the large cloud players are racing to control the foundations of life and the power that comes with such knowledge. They may also reflect that Meta is working double-time to re-shape its image towards the metaverse and this advancement places them very far away from Facebook likes. For me, these concerns are far outweighed by the fact that both Google and Meta have made these tools open source for the scientific community to integrate into labs immediately, and we all stand to benefit from the accelerated innovation from their collective discoveries. Watch this space.

A Sledgehammer to Moore’s Law Limitations

You’ve read up to this point and thought, Allyson I’ve already heard of chatbots and protein folding. True! These have garnered a boatload of attention in their respective circles. But my third technology to watch heading into 2023 is one that quietly launched at Supercomputing last month, the Universal Chiplet Interconnect Express, or UCIe specification. I first wrote about it in the summary of SC22’s advancements and have since got even more excited about its promise after talking to its architects. So what is UCIe, and why am I holding it in such high esteem?

To answer this question, we need to first look at the problem that UCIe and other technologies like the Compute Express Link (CXL) are trying to solve. Moore’s Law is running out of gas, and shrinking process technology, the foundation for computing performance advancement since the birth of the microprocessor, will only get us so far in advancing semiconductor density. While CXL has provided a fantastic industry standard to connect chips on a computing platform and has eliminated historical proprietary interconnect schemes that have gated true heterogeneous computing, UCIe is going a leap further enabling this same industry standard foundation on chip package. What does this mean? Chiplet architectures, first envisioned by DARPA’s CHIPS program back in 2017, can finally be advanced without the limitation of proprietary technology. This means that both industry and consumers of computing can dial in the right balance of CPU, GPU, DPU etc chiplets into a a microprocessing package to deliver the best performance capabilities for targeted workloads. The who’s who of semis have engaged in the UCIe specifications both from a standpoint of silicon suppliers (enter AMD, ARM, Intel, NVIDIA Samsung, TSMC and more) and large service providers with their own silicon aspirations (hello Alibaba, Google, Meta, and Microsoft). Notably absent is Amazon, and we’ll need to watch to see if they really want to fight an standard consensus that seems destined to take off in products across the industry.

So why am I elevating UCIe to this lofty position? Microprocessor advancement is still foundational to breakthroughs of everything that runs on silicon. Without access to more performance our advances will be gated to today’s processing capabilities, and the computing industry sits alone in terms of the rate of innovation enjoyed for decades based on silicon advancement. Further breakthroughs simply require it, and for me that is a big call for applause for the team who delivered the UCIe 1.0 specification. Expect more details on the TechArena soon. As always, thanks for engaging – Allyson.

I love studying the societal disruption that is AI, and we’ve uncovered some phenomenal stories on the TechArena including NASA’s study of global air pollution and Lyssn’s work in improving mental healthcare for all. I’m a strong believer that if we’re to solve the largest challenges facing humanity from climate change to medical breakthroughs artificial intelligence will be at the solution’s core. Of course, AI has disrupted the inspirational to the banal (yes, Amazon, I AM the perfect person for the Dragon Pip plush toy that you’ve recommended) and that is what makes watching its arc so much fun.

One of the better stories in this realm of fun ways AI is improving our existence is WalterPicks. Anyone that knows me knows that I love Fantasy Football and often cajole others into playing through the football season. Draft day is an occasion in the Klein household with experts consulted, statistics vetted, and coffee consumed to ensure that I’m at the top of my game. But what if there was a better prognosticator for draft selections and weekly lineups? I came across the founders of WalterPicks through a small mention in an online story and was wowed. They have developed a model that uses machine learning to predict fantasy football outcomes, and they’re outperforming the big guys Yahoo and ESPN by 17% over the last two years alone.

What’s better, they developed this model out of a passion for the game in a machine learning course at Ithaca college. Did I mention that I love stories like this? Once they put their tool to the test during the season they knew they’d struck fantasy gold. In an industry that is growing past $45 billion by 2027 (a fact that is startling to all who do not play fantasy sports games), WalterPicks could be an essential tool for all gamers hoping to win their leagues. I hope you enjoy the episode and thank you for engaging. - Allyson

TechArena host Allyson Klein chats with WalterPicks co-founder Sam Factor about how AI helps deliver 17% superior recommendations to fantasy football lineups vs. the major recommendation sites.

Improving mental health through AI

As we kick off the holiday season this week with Thanksgiving in the US and Black Friday everywhere it’s important to recognize that this time of year can be more stressful on many. In fact, according to the American Psychological Association, 38% of people surveyed stated that stress increased during the holidays due to time and financial pressures, gift giving and family gatherings. With our mental health providers already stretched by a populace stressed by pandemic and economic concerns, I was curious about what our industry was doing to help. This is when I discovered the team at Lyssn (pronounced listen).

Lyssn was formed in 2017 by a group of psychologists and engineers keen to apply artificial intelligence to improve the quality of therapy and assist practitioners. The underlying technology was born out of a study on AI training of therapists funded by the NIH, but researchers realized they were onto something that could have meaningful application for both public mental health resources and private sector clinics.

One thing that struck me about this company in particular was that the leadership were actually former practitioners themselves making them both better apt to identify the parameters for algorithm training and the mindset for practitioner adoption. In fact, Lyssn co-founder Zac Imel, continues as a professor of counseling psychology at the University of Utah in addition to his responsibilities at the company. Our discussion covered the interesting journey of Lyssn since its foundation, how AI is a resource for therapeutic practice, not a replacement for human-to-human engagement, and how state and local governments and clinics across the nation have signed up for Lyssn solutions.

Listen to the episode to hear how Zac and other researchers trained their models specifically for the therapeutic environment and how AI has evolved in this short time to provide more robust assistance to practitioners tapping natural language processing, to analyze conversations in real time and make recommendations for improving the quality and outcome of the therapy experience. I hope you find this application of AI as inspirational as I did as you consider the real-world impact driven through adoption. Thanks for engaging and Happy Thanksgiving - Allyson

TechArena host Allyson Klein talks with Lyssn co-founder Zac Imel about how his company intends to change the shape of mental health using artificial intelligence.

TechArena host Allyson Klein talks with Ampere Chief Product Officer Jeff Wittich on the rise of Ampere fueled computing in the cloud and why Ampere's lineup places it in an excellent position for the next wave of cloud growth.

It’s hard to believe that cloud computing is turning 25 this year likely signing up for its first 401K and starting to check its credit score. It was in 1997 that Emory University Professor Ramnath Chellapa defined cloud computing as a “computing paradigm, where the boundaries of computing will be determined by economic rationale, rather than technical limits alone.” Soon after Amazon introduced retail-based services, and in 2006 both Amazon and Google made what would be historic moves with the introduction of AWS and Google Docs services. Netflix followed the next year followed by NASA’s OpenNebula in 2008 (remember that?), and enterprises woke up to the fact that their infrastructure was becoming antiquated. With the economic uncertainty facing many organizations in the financial crisis of 2009, new technology alternatives that previously might have seemed risky were now seen as opportunities to build new agility into IT organizations. Private clouds were born, and the Arthurian quest for the perfect hybrid cloud environment was kicked off.

Today we all know the value of cloud. Even people who don’t obsess about tech know the value of cloud services to our lives and how they have fundamentally transformed societal function. We also are all acutely aware of how the past two years of pandemic would have been exponentially worse if not for this technology. As we enter into the post-pandemic world, I wanted to delve deep into where the cloud stands today. Over the following weeks I’ll be sharing opinions on where we are at across infrastructure, software stacks, security, and services from some of the industry’s brightest minds, and we’ll uncover a view on what promising innovations will drive cloud capability forward into the next quarter century of advancement.

I’m kicking off the series with a conversation with Ampere chief product officer Jeff Wittich on the foundational future of cloud processing requirements and why Ampere has built its products from the ground up for cloud workloads. In its fifth year of existence, Ampere has gone from silicon dream to deployment reality at some of the largest cloud service providers on the planet and proven that new architectures (even those not designed in house) can thrive in cloud environments. Jeff also shares his view that we’ve reached another macro environment where economic uncertainty opens the door to new avenues for technology innovation with Ampere products delivering new opportunity for performance and cost efficiency. I invite you all to check out the interview, subscribe to get the entire series, and reach out to me and my guests to continue the dialogue. Thanks for engaging - Allyson

It was incredible to be back at a full-fledged in person SC’22 in Dallas this week. After two years of pandemic-limited interaction, the conference felt vibrant and essential to the sharing of ideas and innovation. I’m back in Portland and reflecting on the advances the largest research institutions have made in the past year with new entries in the Top500, a heightened focus on research collaboration spurred by a period of acute scientific demand from humanity, and a hope for additional collaboration from the industry towards new heterogeneous systems to fuel the proliferation of Exascale computing and beyond. Farther afield, I’m keeping my eye on the advancement of chiplet architectures and how they’ll shape future systems.

Some quick takes from me on the silicon front. Yes, we’re seeing advancement by AMD taking the top spot with the Frontier system and inclusion in over 20% of the newest list of top supercomputers. This was expected, but for me the real story to watch in the coming year is the advancement of heterogeneous systems powered by CXL providing more flexibility in design for matrix and vector processing requirements. The answer is no longer which silicon but what compliment of silicon to provide the flexibility required for diverse HPC workloads. We also saw the announcement of the UCIe 1.0 specification providing an industry standard chiplet interconnect. We’ve talked about chiplets for a while now, but with support from all the major logic vendors AND many of the major cloud providers and integration with CXL for near term volume attach I am anticipating to see some vendor news on integration of UCIe into future products soon. The net net? The customer wins with more flexibility of silicon choice for computing needs and industry innovation accelerates with a standards-based playing field.

Then there’s data. The takeaway is that researchers have a lot of it and need to manage it. I published my discussion with Jeff Denworth, co-founder of Vast Data, on their new universal storage solutions, all flash NAS that creates an efficient and scalable storage alternative. Jeff thinks this will disrupt the memory storage paradigm, and we already know that with CXL invading platforms we’ll see “far memory” designs creating new opportunity for lower latency data delivery as well. In Turing award winner Jack Dongarra’s lecture at the conference, he laid out that this is the bottleneck for HPC systems today which is why I was equally intrigued to see the advancements in the IO500 systems as I was for the Top500. The IO500 organization is publishing interesting data on not only what systems are delivering best bandwidth, metadata performance, and overall performance, they provide a cross-section of which storage platforms were submitted for analysis (with Lustre being the predominant class of storage system for this report). If you’re not familiar yet with IO500, I’d encourage you to dig into the results and review the presentation that they delivered at SC’22.

Finally, there’s the research itself, and this is what makes SuperComputing such an inspirational conference. To hear directly from scientists on the challenges they’re solving with the help of supercomputing is always impressive. One example was Karissa Sabonmatsu’s discussion on her institute at Los Alamos’ progress in unlocking genomes at the atomic level. She described the holy grail of cell level research as studying a single human cell for ten days and requiring 1012 Yottaflops of compute power. The complexity? A single gene represents over a billion atoms, and measuring molecular dynamics for a gene requires > 100 million calculations per second. Sabonmatsu is famous for her study of Ribosomes, those biological elements that connect mRNA and tRNA to synthesize polypeptides and proteins and are central to understanding how living systems operate as well as how drug and vaccine therapies work. The ribosome is a central player in how COVID-19 vaccinations protect us from the virus, and its continued study (and the underlying compute innovation required to continue unlocking it) will assist with creation of other therapies to combat a myriad of diseases.

We also heard from NASA about their research in air pollution and its effect on the planet. My discussion with NASA researcher Megan Damon provided insight in how their supercomputing center is furthering our understanding of the human and natural contributors to air pollution, how these aerosols and particulates travel across the globe, and how they contribute to climate change and human health. One in eight pre-mature deaths are partially attributed to air quality today, so the impact of this research will help us better understand the interrelation between what’s in our air and how we can mitigate impact on humanity. Again, computing has a main role to play in delivering insight to fuel scientists working on this study.

And that’s a wrap from SC’22! Thanks for engaging - Allyson

Tech Arena host Allyson Klein chats with NASA’s Megan Damon on her group’s study of global air pollutants and how supercomputing helps speed insight to global climate change and human welfare.

A good part of the industry is focused on how to contend with data. We all know that we’re creating more of it at an eye-opening rate, but harnessing data for positive organizational or societal value is a non-trivial exercise. Entire industries have been built searching for this holy grail, and as the era of AI dawns upon us our desire to bring larger data sets to bear to solve our largest problems has grown.

There’s no better place to consider data architectures than Supercomputing. This community of the largest compute clusters on the planet knows a thing or two about data at scale, and I was confident that there would be innovation on display in the halls of SC’22. Last night’s plenary session featured some of the leading minds in scientific computing today (more on that in a future post), and one observation that really sunk in was that scientific discovery has fundamentally shifted from finding enough scientists to gather data to focusing scientists to infer the correct correlations from the mountains of data that we have. Industry tools to make this easier on the scientific community would offer the opportunity to more easily curate data and therefore speed insights. This observation in the realm of HPC easily extrapolates to the private sector from enterprise to the largest cloud providers.

I got the distinct pleasure to speak to Jeff Denworth, co-founder and CMO of Vast Data about their innovative approach to data storage…what they call Universal Storage. The Vastronauts have been getting a lot of attention of late for delivering all flash storage solutions that they claim disrupts traditional storage paradigms and provides an easier path for managing large data pools. Garnter placed Vast squarely on their magic quadrant, CRN named them the emerging player of the year…and today HPCWire recognized them for their ascent as a key provider for the HPC arena.

Check out my chat with Jeff where he shares more about the architecture and where the Vast team is seeing deployment interest. Jeff spoke about his background in Lustre and the fact that the Vast solution turns away from more complicated storage topologies with a NAS that is extremely well designed. Aha, THAT simplicity, efficiency and scale are absolutely going to grab attention. I hope you enjoy the discussion. Thanks for engaging. - Allyson

Allyson chats with Vast Data co-founder and CMO Jeff Denworth about Universal Storage and why it aims to disrupt traditional data paradigms.

Turing Award Winner Jack Dongarra Shines a Light on the State of Supercomputing

Today at SC’22 the Turing Award winner, Jack Dongarra of the University of Tennessee, provided a retrospective on high performance computing from its early days to opportunities of the Exascale era. A note on the Turing Award. Named after Alan Turing and often considered a Nobel equivalent for computing, the award goes to a scientist each year who has contributed to the field of computing advancement and comes with a $1,000,000 prize. Past recipients have delivered inventions like the UNIX operating system (Ken Thompson and Dennis Ritchie in 1983), TCP/IP (Vint Cerf and Bob Kahn in 2004), compiler and automatic parallel execution (Frances Allen, the first woman awarded the Turing in 2006), and design of computer architectures (David Patterson and John Hennessy in 2017). These are people who can hush rooms when speaking, and this year’s award recipient is no different.

One could argue that the HPC field and SuperComputing conference itself would be vastly different without Jack Dongarra’s contributions. His continuous investment in eras of HPC development have enabled the scientific community to both maximize the value of infrastructure and measure infrastructure performance. It’s this last bit that offered a unique lesson for those listening to Jack’s talk today. It’s the story of how the Top 500 came into being and really how we have standard benchmarks for everything the computing industry delivers. This, for someone like me who has been in this industry for a minute or two, is like uncovering why water is wet. We care deeply for advancements in performance, and things like benchmarks and the Top 500 give us the fundamental tools to measure advancements in a fair and consistent manner.

So how did this happen? Jack, as one of the founders of Linpack, wrote a simple table to measure a set of complex equations to measure relative performance of systems back in the 1980s. He began maintaining a list of relative performance, and in 1993 merged his efforts with two other scientists’ similar pursuits. The Top 500 was born with a system from Los Alamos Labs at the top measuring a total of 1000 processors busy simulating nuclear warheads. Since then labs vie for top spots on the Top 500, vendors scramble to ensure their infrastructure is featured prominently, and the entire computing industry is pushed forward reaching for more performance to fuel these massive machines. This is a great example of the human motivation driven in part by standard metrics, and we all have to thank Jack and his colleagues for this bar.

So what has happened since the introduction of the Top500? Jack spoke about waves of computing architectural transformations, from shared memory systems in the ‘90s to distributed memory systems of the 2000’s to the introduction of multicore and hybrid architectures in the 2010’s and today the era of exascale fueled by the merger of HPC and AI, the evolution of heterogeneous platforms and ultimately the performance at Exascale (or a billion billion flops). The Exascale Project, with multi-billion dollar funding by the US government, has focused on 21 applications across the realms of scientific exploration with a common theme of 3D model simulation, all benefited by underlying infrastructure advancements and software optimization efforts and contributions from Dr. Dongarra. We’ll continue to see the secrets of the universe unlocked at more rapid rates due to the collective contributions of this HPC community, and for that I’m incredibly grateful.

Still, there are some challenges ahead. The Top 500 has also become a geo-political hot potato. With China holding the pole position with over 160 supercomputers on the list and the US in second position with 125 there is an existential reality that those who can unlock these secrets have power of first action. In fact, there is belief that China holds two Exascale class machines that it has not submitted to the Top 500 list in this era of microprocessor power becoming a strategic national security asset. One need not look farther than recent history of China and technology sanctions and the US CHIPS Act to understand the value of microprocessors to national security interests, and the nexus for this challenge is playing out on the Top 500 list. And in reflecting on this, I can only think back to yesterday’s plenary session at the conference where leaders of supercomputing from ORNL and NIAID called for a new era of collaborative research to solve our most pressing problems. This open and collaborative approach proved to be critical most recently to unlocking the COVID 19 virus and has been a cornerstone of computer aided research since its inception. In this way, the Top500 is providing a different kind of transparent measurement, one that shines a light on how geopolitical concerns can stand in the way of societal advancement. I’m hoping that the spirit of Jack Dongarra and his fellow Turing Award winners prevail to all of our benefit. Thanks for engaging. - Allyson

Welcome to the Tech Arena, a new media platform delivering authentic conversations with the leading technology innovators. As a veteran of the industry, having worked on innovations as far reaching as cloud computing, 5G networks, and AI, I have heard a lot of stories from companies inventing technology and those tapping this technology to create business opportunity or societal advancement. I’m a great believer that technology is the foundational change agent in society today, so the work being delivered across the tech arena is inspirational. The stories we hear, however, can sometimes be pigeonholed into overused hero vs villain archetypes or perhaps stories that are uniquely focused on a subset of our true community. There are other voices out there just waiting to be heard.

I left my corporate career after leading organizations at some of the largest names in tech to launch the TechArena because I strongly believe that we’re all seeking a different dialogue. One that isn’t afraid to highlight stories from both tech titans and scrappy disruptors delivering something that will push us all forward. We’ll roll up our sleeves and go two clicks down to not just discuss the what but also the how and why of an innovator’s aim and intention. And you’ll hear a broader array of voices on this channel…yes, the women of tech including yours truly, but also a diversity of technology roles, teams from locations across the globe, and stories that may not have be grabbing the headlines but have the opportunity to push us forward to the benefit of all.

There was no better place to launch the TechArena for me than Supercomputing 2022. This annual conference features not only the largest scale computing on the planet, it is also a nexus for the scientific community to congregate to discuss what insights were delivered to us in the past year due to the contributions of technology and what they collectively need from the tech industry to reach those next exploration breakthroughs. Today’s targets focus on unlocking the foundations of life, mitigating climate impact and exploring the farthest reaches of the galaxy. This week, I’m looking forward to hearing more about infrastructure advancements to address the convergence of HPC and AI, how we’ll meet the growing challenge of energy efficiency for large scale compute clusters, and how we’ll continue to feed larger and larger models for research team analysis.

So check out the podcasts, blogs and content drops, please follow the TechArena on Twitter, LinkedIn and other social sites, and subscribe to our feeds on Soundcloud, Substack or wherever you get your content. And I’d love to hear from you with feedback on this program, interest in collaborating, and suggestions about who you’d like to see in the arena. Thanks for engaging. - Allyson

Allyson steps into the arena with British physicist Jess Wade to discuss her advocacy for under-represented STEM recognition through Wikipedia biography publication.

To be seen is a first step to true inclusion, and in 2022 I’m regularly struck by how we still collectively struggle to see one another and our respective contributions to our respective fields. This is a primary reason when founding the TechArena that I decided to establish a platform for stories that help gain more collective appreciation for individuals and teams who may be otherwise overlooked. It’s also why I was strongly drawn to the story of Jess Wade, a physicist at Imperial College London.

To say that Jess is a badass is an understatement. At the Blackett Laboratory, her research focuses on polymer-based organic light emitting diodes…or the technology that fuels the displays that we spend our lives staring at from smartphones to televisions. At thirty-four, she’s well published and on her way to an extraordinary career of contribution like many Imperial College scientists who came before her. But what’s interesting about this story is that Jess was brought to the TechArena and to the world’s attention for what she does in her off hours.

Jess has always been an advocate for inclusion having learned early in life that the STEM field was narrowly represented based on gender, race, and socioeconomic privilege. A few years ago, she decided to dial up her efforts by addressing the recognition gap, or more specifically, the missing stories of minority scientists from Wikipedia biographies. Today, women make up only nineteen percent of all biographies on Wikipedia, and the numbers for STEM related biographies are even worse. Jess decided to do something about this and dedicated herself to writing a Wikipedia biography every day to shine a light on the incredible scientific contributions that were made by people who, for whatever reason, were not seen fully for their research. Some interesting things have happened since that you can learn more about in our chat. Jess has also garnered some individual attention for her work winning a bevy of awards including being named one of Nature magazine’s 10 people who mattered in science in 2018 and winning the British Empire Medal in 2019.

While Jess shared a lot of great insight during our discussion, the thing that made me decide to bring this story to my Supercomputing publications was her observation that “we're really not designing the best tech solutions to all of these huge global challenges if we're only selecting our big coders or our problem solvers from a handful of the population.” This is not solely a feel-good story about delivering recognition, it’s a story of how we collectively reach farther and better to new insight and discovery of our most pressing global challenges lifted up by all of our collective perspectives. I was heartened to see a wealth of diverse technologists and scientists from a broad range of fields represented in SC’22 agenda and am looking forward to seeing if this is reflected in the conference proceedings as a whole. If you’d like to share your perspective on this important topic please connect on Twitter or LinkedIn.