MapD @ MIT-CHIEF by MIT-China Innovation and Entrepreneurship Forum

MapD @ MIT-CHIEF by MIT-China Innovation and Entrepreneurship Forum
A talk with Todd Mostak, Founder & CEO on August 17, 2017.

Please check out this deck and learn more about MapD and the world-class open source GPU database and visualization platform for real-time analytics that they are bringing to the market.

For more information, please find them on Twitter: @MapD or email info at Map D dot com. Thank you. http://www.mapd.com

MapD Technologies
Founded 2013 in Boston and later relocated to San Francisco, MapD got $10M series A and $25M series B funds from Google Ventures (GV), Nvidia, New Enterprise Associates, Vanedge Capital, Verizon Ventures and more. MapD harnesses the massive computing power and memory bandwidth of commodity GPUs to build the next generation open-source database and big data platform that can be used to visualize billions of data points in milliseconds.

Todd Mostak
Todd is the CEO and Founder of MapD Technologies. He built the original prototype of MapD after getting tired of the inability of conventional tools to allow for interactive exploration of big data sets while conducting his Harvard graduate research on the role of Twitter in the Arab Spring. He then joined MIT as a research fellow at CSAIL focusing on GPU databases before turning the MapD project into a startup.

Transcript

2. 2 Confidential & Proprietary The long road from the Arab Spring to Silicon Valley ?
3. 3 Confidential & Proprietary GPUs offer a way forward GPU Processing Power 50% per year Data Growth 40% per year CPU Processing Power 20% per year
4. 4 Confidential & Proprietary MapD: software optimized for the fastest hardware + 100x Faster Queries Speed of Thought Visualization MapD Core MapD Immerse An in-memory, relational, column store database powered by GPUs A visual analytics engine that leverages the speed + rendering capabilities of MapD Core
5. 5 Confidential & Proprietary Who is MapD? MapD was incubated in the MIT CSAIL database group under the advisory of Michael Stonebraker and Sam Madden (Vertica). MapD has captured the imagination of some of the most sophisticated investors in Silicon Valley and beyond. “It's completely amazing
6. 6 Confidential & Proprietary TCO SPEED
7. 7 Confidential & Proprietary TIME 1991 2017 GPU’s will be as transformative to Analytics, as Broadband was to the Internet Analytics ANALYTICS 3.0 ACCELERATED/ENRICHED ANALYTICS 2.0 ANALYTICS 1.0 Why MapD?
8. 8 Confidential & Proprietary Where does MapD fit in? Complementing your entire data ecosystem JDBC Kafka MapD  C ore  Database Data  Warehouse Data  Lake,  HDFS Streaming  Data JDBC, ODBC, Thrift MapD  Immerse  C lient GDF, Thrift Continuum,  H20, TensorFlow Machine  Learning Python,  R Data  Science GPU  ACCELERATION Output Input 3rd  Party  Viz C ustom  Apps SQL Rendering  Engine Tableau,  Power  BI
9. 9 MapD Core 9 The world's fastest in-memory GPU database powers the world's most immersive data exploration experience
10. 10 Confidential & Proprietary Keeping Data Close to Compute
11. 11 Confidential & Proprietary 10111010101001010110101101010 101 00110101101101010101010101011 101 Query Compilation with LLVM Traditional DBs can be highly inefficient •  each operator in SQL treated as a separate function •  incurs tremendous overhead and prevents vectorization MapD compiles queries w/LLVM to create one custom function •  Queries run at speeds approaching hand-written functions •  LLVM enables generic targeting of different architectures (GPUs, X86, ARM, etc). •  Code can be generated to run query on CPU and GPU simultaneously
12. The table is sorted by the fastest time query 1 finished in (measured in seconds). The Fastest Database MapD’s innovation drives exceptional speed, scale and ROI Confidential & Proprietary 12 Noted DB blogger, Mark Litwintschik has benchmarked MapD vs. major CPU systems on a billion row taxi data set and found it to be between 74x to 3,500x faster than CPU DBs. * pre-computed date intervals
13. Confidential & Proprietary 13 GOAI: End-to-end analytics on the GPU GPU Open Analytics Initiative – Fusing Machine Learning and GPU Analytics
14. 14 MapD Immerse Lightning fast visual analytics for the MapD Core database
15. Confidential & Proprietary 15 Basic charts are frontend rendered using D3 and other related toolkits Scatterplots, pointmaps + polygons are backend rendered using the Iris Rendering Engine on GPUs Geo-Viz is composited over a frontend rendered basemap MapD Immerse: our hybrid approach
16. HOW IS MAPD ! BEING USED?! !
17. Confidential & Proprietary 17 How is MapD being used?
18. Confidential & Proprietary 18 How is MapD being used?
19. Confidential & Proprietary 19 How is MapD being used?
20. 20 Confidential & Proprietary TELECOMMUNICATIONS Predictive Network Performance Customer Churn ENERGY Dynamic Oil Well Management How is MapD being used?
21. 21 Confidential & Proprietary MapD Customers
22. 22 Confidential & Proprietary MapD, Now Open Source
23. 23 DEMO
24. 24 Confidential & Proprietary Closing thoughts We are at an inflection point in compute and GPUs are set to dominate the coming decade.
25. 25 Confidential & Proprietary GPUs allow users to scale up before needing to scale out. lowering performance-killing network overheads and decreasing hardware and administration costs. Closing thoughts
26. 26 Confidential & Proprietary Closing thoughts Integrated Analytics on GPUs comprising querying, viz and ML provide critical efficiencies and capabilities not found in siloed systems.