The diversity of compute workloads like machine learning, big data analytics, and streaming video in the modern datacenter has increased the load on the server CPUs. Scaling todays infrastructure cost-effectively requires smart adaptive inline storage processing that offloads the over-burdened server CPU in the datacenter. In this keynote, we highlight how our adaptable, extensible and high-performance storage platform lays the groundwork for computational storage for the data-centric era. The platform leverages Xilinx state-of-the-art IP portfolio and industry-leading tools. We showcase customer products across a range of applications such as data analytics and video processing that are making this vision of computational storage a reality.
Booming growth in both compute and storage have effectively changed how best to tie the traditional SW and HW layers together for scale, as well as which new SW and HW layers to use. This have given rise to the demand for a new paradigm in the data center. Composable infrastructure takes into consideration:
- Strategic changes in storage device functionality,
- Form factors and capacity points
- New compute platforms
The result? Hardware that performs compute with open source hardware and software, combined with new more functional and powerful networks.
In this presentation, the interactions and benefits of new data center components, and their role in a new, more efficient datacenter, built around composable infrastructure will be explored with an inspiration to rethink compute.
This will be remembered as the decade that AI achieved the predictive power of primary sciences such as physics, chemistry, and biology. Modern AI is now able to make to make projections with unprecedented accuracy across a huge number of domains. This is accomplished by using data to learn true underlying mechanisms for each bespoke problem, mirroring the way sciences and engineering are based upon foundational theories, such as quantum mechanics for physics, the periodic table for chemistry, and DNA/RNA for biology.
This talk presents a technically-inspired explanation for newcomers of how the recent breakthroughs in AI enable this capability, how they are being used, and shows that there will be a generational-level revolution in the coming decades. Numerous application examples demonstrate these new AI techniques, and how they are transforming domains such as manufacturing, medicine, financial services, cybersecurity, retail and online marketing, and even physical sciences.
We cover how Big Data is the fuel of this new AI, allowing enterprises to tap more deeply into the knowledge locked in their data, in ways often not possible with traditional data analytics. We peer into the future implications for data storage, revealing likely secular trends that will emerge, driven by this revolution shaping the way data is utilized by future enterprises.