3D NAND Technology Scaling helps accelerate AI growth

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3D NAND Technology Scaling helps accelerate AI growth Jung Yoon, Ranjana Godse IBM Supply Chain Engineering Andrew Walls IBM Flash Systems August 2018 1

Agenda 3D-NAND Scaling & AI Flash density trend NAND Layer Count scaling trend $/GB trend NAND technology Bandwidth comparison Flash Energy/Power trends Summary August 2018 2

Where do AI algorithms run? Artificial Intelligence (Any technique that enable computers to mimic human brain) Machine learning (Any technique that learns using statistical methods) AI on cloud AI on Edge Deep Learning (Multi layered neural network exposed to vast amount of data) August 2018 Deep learning multilayered neural network require high throughput data ingestion, lower power consumption, small system footprints, and lower system cost - AI acceleration to be realized by 3D-NAND scaling 3

Characteristics of AI Deep Learning, Machine Learning and all forms of Analytics on Data requires ingestion of large amount of data at very high throughput Real time AI require data pattern & relationship learning Workloads tend to be In-Memory database centric need to ingest data at high rate & throughput To have a large dataset it requires lots of memory and lots of servers. DRAM is extremely expensive, challenges with bit cost reduction via scaling As data sets used for training ML/DL are growing over time Flash with its low latency & high throughput is most optimal solution for AI storage August 2018 4

Attributes of AI Flash has very high read throughput density to assist workloads like deep learning Real Time analytics require low latency access to lots of data. e.g., credit card fraud detection, image recognition Flash with increasing density can allow for lots of data to be accessed at fairly low latency Flash enables High IOPs with low read latency, smaller footprint and lower power compared to HDD Low Latency NAND and SCMs - fill performance and cost gap between Memory and Storage August 2018 5

3D-NAND Scaling & AI 3D-NAND technology scaling provides high throughput density, lower power consumption, and smaller system footprints critical to accelerating AI growth 3D-NAND enables multi-terabit TLC and QLC densities through cell layer count increases, innovations in circuit design, process technology, and stacked packaging The resulting cost reductions, throughput increases, and lower power consumption enable flash driven AI growth. Density, performance, and reliability tradeoffs must be considered for TLC, QLC, MLC, and low latency NAND. High throughput data ingestion and system reliability requirements for AI optimized workloads critical August 2018 6

Memory density trend Flash density growth will continue via 3D NAND layer count scaling 2018-2022+ - TLC, QLC, LL-NAND 3D NAND scaling on a 18-24 month cadence thru 2020 64L > 96L >120L >190L Flash with increasing density can allow for lots of data accelerating AI growth August 2018 7

Layer count trend for 3D NAND Ref: 3D NAND process trends. TechInsights 3D-NAND scaling expected to continue via 3D Layer count increase >200 layers & lithography shrink in 2022+ & beyond no need for EUV for 8+ years in flash Significant 3D-NAND Process, Architecture & Cell materials innovations needed for continued >200Layer scaling August 2018 8

3D NAND Scaling Process challenges Ref: T. Lill LAM Research, FMS2017 Increase in number of layers make the high aspect ratio etch challenging-z-directional 3D-NAND cell process controls become critical with multiple etch processes Process innovations required in High AR Channel Etch, Stair case contacts, defect control, wafer yield August 2018 9

$/GB trend for DRAM, NAND, SCM Flash Market Demand growth driven by high density 3D NAND bit cost scaling with increased layer count Strong penetration of 3D TLC & QLC in Cloud Datacenter & Enterprise Storage in 2018-20 3D-NAND scaling enabled bit cost reduction combined with low latency, high throughput accelerating flash driven AI growth August 2018 10

Density Growth for SSD and HDD Density (TB) 71 61 51 41 31 21 Density growth for SSD and HDD 11 3.5" HDD 2.5" SSD 1 2014 2015 2016 2017 2018 2019 2020 2021 Year 1.00E-02 1.00E-03 1.00E-04 1.00E-05 2014 2015 2016 2017 2018 2019 2020 2021 Year 3.5" HDD 2.5" SSD August 2018 11 Cubic Density (TB/mm3) Cubic Density for SSD and HDD Drastic increase in Flash-SSD vs HDD in the past 5 years. SSD density growth driven by increase in number of layers and capacity for 3D TLC and QLC NAND Flash-SSD enables smaller system footprint over HDD flash driven AI system acceleration (Petabytes of storage can be put in single rack-mount enclosure)

Density growth for 3D NAND Max Flash memory density/mm3 in 16DP stacked Package Max Flash memory density/mm2 in 2D Si area Increase in 3D-NAND layer count drives significant increase in Si density/mm2 & Package density/mm3 3D-NAND scaling density/mm3 increases driving significant storage system footprint efficiencies optimal for AI Storage solutions August 2018 12

NAND technology vs. Bandwidth Bandwidth is the maximum amount of data that can travel through the channel. Complex workloads and volume of data is feed to Deep learning set. Thousands of threads processing this massive data have to reply on high data delivery rate from storage Flash has a very high read throughput density (over HDD) - optimal for deep learning workloads August 2018 13

NAND technology Energy trend 122 4221 *,%-& ("#$%&'/)'*$),%-&%./ = 6.&$ 789$ ("#$%&'/)'*$)%$.: = 122 4222 *%$.: 6.&$ 789$ With 3D-NAND generations, program and read Energy decreasing trend Flash consumes less power vs HDD significant difference in cost at large scale AI storage systems August 2018 14

NAND technology Energy trend Assuming 8% Read, 23% Program and 14% Erase workload August 2018 15

Summary AI growth will be accelerate by 3D-NAND technology scaling via high throughput density, lower power consumption, and smaller system footprints 3D-NAND enables multi-terabit TLC and QLC densities through cell layer count increases, innovations in circuit design, process technology, and stacked packaging. The resulting cost reductions, throughput density increases, and lower power consumption expects to enable significant flash driven AI growth. August 2018 16