Achieving Energy Efficiency in Data Storage for the Zettabyte Era

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1 Achieving Energy Efficiency in Data Storage for the Zettabyte Era Peter Hormann and Leith Campbell November 2014

2 The Digital Universe is Expanding Source: EMC Digital Universe Research & Analysis by IDC (7 th annual study) April

3 How much data? TERABYTE PETABYTE EXABYTE ZETTABYTE 1x x x x TB a digital library of all catalogued books in all languages. ~250 DVDs 100 PB amount of data produced in a single operational minute of the new CERN particle collider. 5 EB text transcript of all words ever spoken. 2 EB est. current daily growth in data stored (2013). Amount of data that has traversed the Internet since its creation. ~250 billion DVDs. Source: Cisco Visual Networking Index (VNI) June

4 Introduction Business as usual approach to storing data is not sustainable. Not possible to have all data online and available forever. Industry and individual behaviour change required. 4

5 Data Migration to the Cloud / Data Centre Readily available and cheap (if not, perceived as free)! Evolution of cloud-based applications and storage services o Gartner migration of Personal Computer to Personal Cloud (2012) Seagate shipped storage capacity (2014): o % to client end-user devices o % to cloud / data centre 5

6 What do we know already? Koomey. Growth in data center electricity use 2005 to 2010 (2011) o Data storage treated at a very high-level and linked to growth in compute capacity. Van Heddeghem et al. Trends in worldwide ICT electricity consumption from 2007 to 2012 (2014) o Top down approach based on estimated physical server counts / types data storage treated as an overhead. Linkage between compute/storage is weakening given drive to virtualisation. 6

7 What do we know already? GeSI Smarter 2020 (2012) o Global Data Centre power consumption based on Koomey with growth factors - Data storage growth factor - 20x (from Cisco). o Forecast for 2020: - Total GDC Power = 480 TWh, PUE = ICT Infra. Power = 347 TWh Under what scenarios will (or won t) this forecast be achieved? 7

8 Digital Universe Study (TB) Shipped Data Storage Forecasts (%) Storage Technology Roadmap Storage Tech. Energy by Type (W/TB) What did we do? Normalisation of forecasts to (TB) Scenario Storage Tier Mix (%) Storage Tier Power Calculation (W/TB) Results Data Centre Forecasts (TWh) For comparison

9 Digital Universe Study (TB) Shipped Data Storage Forecasts (%) Storage Technology Roadmap Storage Tech. Energy by Type (W/TB) What did we do? Normalisation of forecasts to (TB) Scenario Storage Tier Mix (%) Storage Tier Power Calculation (W/TB) Results Data Centre Forecasts (TWh) For comparison

10 In the beginning 1956 A 5 megabyte IBM Hard Disk Drive (HDD) is loaded into an airplane Weight: 1000kg Cost: US$50,000 Source: /photo/1 (4-Jan-2014) 10

11 Forklift to Fingertips! Solid State Memory RRP AU$175 ($1.37 / GB) Source: (19-May-2014) 11

12 A History of Data Storage Costs 2014: US$0.03/GB Source: (Matt Komorowski 9-Mar-2014) 12

15 Digital Universe Study (TB) Shipped Data Storage Forecasts (%) Storage Technology Roadmap Storage Tech. Energy by Type (W/TB) What did we do? Normalisation of forecasts to (TB) Scenario Storage Tier Mix (%) Storage Tier Power Calculation (W/TB) Results Data Centre Forecasts (TWh) For comparison

16 Data Storage Hierarchy Increasing energy efficiency (Wh/TB/yr) Increasing frequency of data access (never again to many) Increasing Performance (IOPS) Increasing Purchase Price ($) Tier 4 Tier 3 Tier 2 Tier 1 Tier 0 SSD High Perf. HDD/SSHD Capacity HDD Solid State Drive Near Online HDD (MAID Massive Array of Idle Disks) Solid State Hybrid Drive Offline Removable Media (tape, optical disks) Hard Disk Drive Increasing latency (micro seconds to days/weeks) Decreasing embodied energy Decreasing Operational Cost ($/pa) Increasing data lifetime (nano-seconds to 1,000 years) Tier 5 Warehoused Removable Media (tape to 30 years, optical disks to 1,000 years) Increasing technology lifespan (1 to 1,000 years) 16

17 Average Energy Efficiency of Data Tier Average Energy Efficiency (W/TB) Average Energy Efficiency (W/TB) 0. SSD Hi-perf HDD / SSHD Capacity HDD MAID HDD Removable (tape/optical disk) SSD:HDD $/TB still about 10:1 3TB HDD $150 1TB SSD $500 17

18 Possible Futures Scenarios Scenario Proportion of Digital Universe in 2020 (%) Global Data Centres Data storage capacity growth Business as Usual Continues 40% 10.0x 2. GeSI 20x 33% 8.2x 3. BAU-60% 4. Improved 60% 15.0x 5. Best Likely

19 Proportion of Deployed Capacity Global Data Centre Data Storage Tiering Capacities (%) by Scenario 100% 90% 1% 1% 1% 5% 5% 5% 80% 34% 22% 70% 52% 60% 22% Tier 0 - SSD 50% 20% Tier 1 - Hi Perf HDD/SSHD 40% 12% Tier 2 - Cap. HDD Tier 3 - Idle HDD 30% 20% 10% 30% 40% 50% Tier 4 - Removable 0% 3.BAU-60% 4.Improved 5.Best Likely Scenario (where 60% of the Digital Universe is in the Data Centre) 19

Proportion of Deployed Capacity Global Data Centre Data Storage Tiering Capacities (%) by Scenario 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 1% 1% 1% 5% 5% 5% 52% 12% 30% 34% 20% 40% 22% 22% 50% 26ZB

20 Proportion of Deployed Capacity Global Data Centre Data Storage Tiering Capacities (%) by Scenario 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 1% 1% 1% 5% 5% 5% 52% 12% 30% 34% 20% 40% 22% 22% 50% 26ZB GDC Total Data 7ZB Online 6ZB Idle Tier 0 - SSD Tier 1 - Hi Perf HDD/SSHD Tier 2 - Cap. HDD Tier 3 - Idle HDD Tier 4 - Removable 13ZB Offline Cold storage 0% 3.BAU-60% 4.Improved 5.Best Likely Scenario (where 60% of the Digital Universe is in the Data Centre) 20

21 Power (GW) Global Data Centre Data Storage Power (GW) Doe 10 5 Not including PUE overheads Year BAU-60% 4.Improved 5.Best Likely

22 Smarter 2020 Comparison Scenario 1. Business as Usual (BAU) Continues Data storage capacity growth Global Data Centres Data storage % of total GDC ICT infra. Load [cf. Smarter 2020] 10.0x 68% 2. GeSI 20x 8.2x 58% Compute & Network Data Storage 3. BAU-60% 107% 4. Improved 15.0x 75% 5. Best Likely 52% Not including PUE overheads 22

23 What do we need to do? If IDC Digital Universe and Seagate shipped capacity forecasts are correct, then business as usual growth of online data storage energy will become unsustainable. GeSI Smarter 2020 forecast achievable if substantial volumes (> 72%) of data is moved to idle or offline cold storage (if not purged). Good information lifecycle governance is critical Other benefits for purging and archiving more data 23

24 What do we need to do? Aggressive deployment of latest technology will help. Most importantly Industry and individual behaviour change is required o Accept not all data has value and needs to be kept o Purge data of little or no value o Archiving data that really needs to be kept 24

Case studies in energy consumption of Internet services: Kerry Hinton CEET University of Melbourne Australia

Case studies in energy consumption of Internet services: Kerry Hinton CEET University of Melbourne Australia Normalised increase The future energy efficiency gaps Current data growth rate >> traditional