©2016 MapD. 1

The Promise of GPU Analytics (or why GPU is the new CPU)April 7, 2016Todd Mostak, CEO, MapD Technologies

©2016 MapD. 2

Real-time decisions require highly interactive querying & visualization of big datasets.

But…

Pain point: Impossible on today’s CPU in-memory DBs due to low compute/memory bandwidth.

©2016 MapD. 3

Why Databases Moved In-Memory

• 2005 – Databases move off disk– Vertica, SAP HANA, ParAccel,

Vectorwise– Driven by cheap memory– Dovetails move to column stores

for analytics• Applications see 30-100X

speedups– Mirrors bandwidth difference

between RAM and disk

©2016 MapD. 4

What’s next: GPU In-Memory Databases/Analytics

• GPU memory density increasing, price decreasing

• GPU memory bandwidth rapidly increasing

• High GPU compute bandwidth

• Promises another 30-100X

©2016 MapD. 5

The Chasm

Broadwell Xeon (2-sockets)

Pascal P100 (8 –cards)

Compute (TeraFLOPS, SP)

~2-4 84.8

Memory Bandwidth (GB/sec)

150 5,760

©2016 MapD. 6

GPU processing

The Chasm

20 cores

CPU processing

39,936 cores

©2016 MapD. 7

MapD: Leveraging Multiple GPUs per Server

Column-StoreDatabase &Rendering Engine

Up to 16 Nvidia GPUs per server

• Fast: 100X+ quicker queries• Leverages GPU rendering for live visualizations of

billions of data points• Less hardware, energy, space, maintenance

©2016 MapD. 8

MapD vs Leading Databases

©2016 MapD. 9

MapD Demo

©2016 MapD. 10

The Need for Speed

How MapD achieves its speedups

• Leverages compute and memory bandwidth of multiple GPUs per server

• Partitions and caches hot data in GPU RAM

• Runs on both CPU and GPU

• Dynamically compiles queries into CPU/GPU Code

• Vectorizes query execution

©2016 MapD. 11

MapD frontend• Complex viz, geoviz, charts

Where MapD sits

Principal data store• MemSQL, HDFS or other DB

GPU database• Up to 192 GB memory

GPU-rendered

Tableau or 3rd party viz

ODBC/Thriftconnectors

Non-graphical output

Database

General DataVisualization

Massive DataVisualization(billions of rows)

©2016 MapD. 12

Why now?

Technology

• Higher GPU density + memory sizes now handle most datasets

• CPUs hitting Moore’s law

• GPUs becoming mainstream in enterprise

Market

• Data volumes/velocity exploding

• Heightened need for real-time decision making

• Surge in sensor and geo data

©2016 MapD. 13

Prepared for In-Q-Tel

October 2015

Thank you

©2016 MapD. 14

The Query Pipeline

GPU

SQL Exec Pipeline

SQL Exec + Render Pipeline

MapD web client

SQL + render

SQL-onlySQL-only or SQL + render

Image tilesor Video

Resultstable

Database

Frontend