https://siliconangle.com/2024/08/23/high-performance-computing-ai-innovation-efficiency-aihardwareandinfrastructure/

Three insights you might have missed from the AI Infrastructure Silicon Valley event

3. As AI infrastructure evolves, new technologies allow enterprises to scale more efficiently by optimizing resource usage, enhancing performance and reducing costs — unlocking new opportunities for productivity and innovation across sectors.

The need for integrated, high-performance systems has never been more critical as AI advances, leading to cutting-edge technologies that supercharge AI infrastructure, such as Celestial AI’s Photonic Fabric. Meanwhile, Pure Storage Inc.’s innovative approach to storage is designed to ensure that storage solutions remain up-to-date and efficient without the need for costly replacements.

“Hardware and systems are cool again,” said Charles Giancarlo, chief executive officer of Pure Storage. “A lot of this is being driven by the excitement around AI but also the recognition that what’s going on in data centers, what’s going on in the world of compute, is accelerating at this point and creating a lot of opportunity for productivity for businesses and for people alike. What we’re seeing in the AI space is that it’s opening up multiple layers of opportunity.”

Similarly, Photonic Fabric, an optical interconnect technology platform, connects AI accelerators using photonics, offering high bandwidth, low latency and low power interconnectivity, according to Dave Lazovsky, co-founder and CEO at Celestial AI. These features are essential for advancing AI performance to the next level.

TheCUBE Research’s John Furrier and Dave Vellante talk with Pure Storage’s Charles Giancarlo about the evolution of storage hardware in hybrid environments.

“What the Photonic Fabric enables is not just an increase in the energy efficiency in the performance associated with compute-to-compute fabric interconnectivity, but, because we have a technology platform that enables bandwidth that is equivalent or superior to HBM3 or HBM4, we have the ability to disaggregate memory,” Lazovsky said. “Photonic Fabric enables it with optically interconnected HBM.”

As enterprises seek to optimize their AI infrastructure, they are increasingly focusing on high-performance computing solutions that are sustainable, scalable and capable of adapting to changing needs. The evolution of storage toward more flexible solutions, such as Pure Storage’s virtualized systems, aligns with the broader industry trend of reducing redundancy and improving data accessibility for AI models.

“We’re creating an environment where on our arrays — all of that data — appears as a pool of data,” Giancarlo explained. “It’s accessible by AI — what AI wants is access to data. Now you have to have the proper security mechanisms in there, role-based access controls, but then you want to allow it to have access to the data where it sits instead of having to be able to replicate it.”

In parallel, Photonic Fabric addresses the growing demand for efficient memory scaling, providing a pathway to manage AI computing workloads more effectively without relying heavily on traditional GPU-based memory controllers. This approach enhances performance and reduces costs associated with AI infrastructure by optimizing resource usage.

“There’s two drivers for the package getting bigger,” Lazovsky said. “It’s an increase in the compute horsepower per package … so there’s a need for more and more high bandwidth memory across AI acceleration systems. By eliminating the use of GPU as the world’s most expensive memory controller, if you don’t need the flops and you’re just buying GPUs for memory capacity, there’s a more efficient way to do it.”