downloadGroupGroupnoun_press release_995423_000000 copyGroupnoun_Feed_96767_000000Group 19noun_pictures_1817522_000000Group 19Group 19noun_Photo_2085192_000000 Copynoun_presentation_2096081_000000Group 19Group Copy 7noun_webinar_692730_000000Path
Skip to main content

Session 3: Technology

Memory and Data Economy: Time to Enable the Simultaneous Causal Relationship

Naga Chandrasekaran, PhD
Senior Vice President, Process R&D and Operations
Micron Technology

Memory demand has seen significant growth over the last decade, to enable and meet current growing data economy. This demand growth has been supported through faster cadence of geometry scaling and design innovations, to enable more bits per wafer, resulting in bit cost reduction. In parallel, memory performance requirements and quality expectations continue to grow at a tremendous pace, to support modern day computing, new applications, and enhanced user experience.  To keep up with demand while addressing increased process complexity and performance requirements, the memory industry and supporting eco-system must deliver new and innovative solutions. This requires continued partnerships across the value chain.

 While continuing our search for solutions in the space of materials, equipment, process, design, and systems, we must rethink how we conduct technology development and implement our solutions. Even though the semiconductor industry has enabled our data economy, as an industry we are only scratching the surface to reap the benefits of data science to address our own challenges. We must turn our collective focus to data science, more specifically, how to effectively utilize the power of data to improve our performance, timeline, and cost.  Collectively, we face the challenge of bringing all streams of data together to deliver value across the supply chain, and eventually to our customers.   Beyond the technology scaling benefits, such efforts can also enable sustainable technology solutions, which can strengthen our future.

Memory demand has seen significant growth over the last decade, to enable and meet current growing data economy. This demand growth has been supported through faster cadence of geometry scaling and design innovations, to enable more bits per wafer, resulting in bit cost reduction. In parallel, memory performance requirements and quality expectations continue to grow at a tremendous pace, to support modern day computing, new applications, and enhanced user experience. To keep up with demand while addressing increased process complexity and performance requirements, the memory industry and supporting eco-system must deliver new and innovative solutions. This requires continued partnerships across the value chain.

While continuing our search for solutions in the space of materials, equipment, process, design, and systems, we must rethink how we conduct technology development and implement our solutions. Even though the semiconductor industry has enabled our data economy, as an industry we are only scratching the surface to reap the benefits of data science to address our own challenges. We must turn our collective focus to data science, more specifically, how to effectively utilize the power of data to improve our performance, timeline, and cost. Collectively, we face the challenge of bringing all streams of data together to deliver value across the supply chain, and eventually to our customers. Beyond the technology scaling benefits, such efforts can also enable sustainable technology solutions, which can strengthen our future.