the promise of gpu analytics (or why gpu is the new...
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©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