WirelessWeek, “What Is a GPU and Why Should Telcos Care?”
2017-03-03 – While 2016 was the year of the GPU for a number of reasons, the truth of the matter is that outside of some core disciplines (deep learning, virtual reality, autonomous vehicles) the use of GPUs for general purpose computing applications is still in its early stages, despite its exceptional growth over the past 12 months.
IBM Bluemix Blog, “Bringing the power of GPUs to cloud”
2017-03-01 – The GPU was invented by NVIDIA back in 1999 as a way to quickly render computer graphics by offloading the computational burden from the CPU.
SearchDataCenter, “GPU-accelerated computing makes its way into the data center”
2017-02-16 – New type of database-analytics platform queries and maps billions of data points in milliseconds.
MIT News, “Split-second data mapping”
2017-01-11 – New type of database-analytics platform queries and maps billions of data points in milliseconds.
InformationWeek, “GPU Hardware Powers MapD Big Data Management”
2016-12-21 – When it comes to clickstream data, server log analysis or machine learning, there's a likely GPU-based system in IT's future.
InfoWorld, “MapD database extends GPU power to AWS, Google Cloud”
2016-12-13 – Version 2 has faster queries and a new web-based visualization tool, with plans to spread to Microsoft Azure too
NetworkWorld from IDG, “New products of the week 12.12.16”
2016-12-12 – MapD Core database and Immerse visual analytics platform
Silicon Angle, “Graphics processor services coming to Google Cloud in 2017”
2016-11-24 – Google Inc. early next year will start offering graphics processing unit chips as a computing service alongside the standard processors in its cloud computing platform, in an effort to make it easier for enterprises to use machine learning.
Google Cloud Platform Blog, “Announcing GPUs for Google Cloud Platform”
2016-11-15 – CPU-based machines in the cloud are terrific for general purpose computing, but certain tasks such as rendering or large-scale simulations are much faster on specialized processors.
Datanami, “Polling Data Hidden in Plain Sight”
2016-11-10 – The gnashing of teeth you may be hearing is the sound of political pollsters whose elegant models completely missed the surge of popular discontent in the hinterlands that propelled Donald J. Trump to the U.S. presidency.
Business Insider, “Silicon Valley is betting its money on Hillary Clinton”
2016-11-07 – As we head into Election Day, one way to figure out which candidate has a leg up is to "follow the money."
Datanami, “Data Visualizations Follow the Campaign Money”
2016-11-02 – The cottage industry of political polling is approaching a fever pitch at the end of a long, tortuous U.S. presidential campaign.
Datanami, “Why America’s Spy Agencies Are Investing In MapD”
2016-10-20 – In-Q-Tel, the venture arm of American spy agencies, announced yesterday that it has invested in MapD.
Defense Systems, “CIA investor backs geospatial data startup”
2016-10-20 – When the CIA's venture capital arm invests in a technology startup, it tends to draw attention.
The Wall Street Journal, “CIA’s In-Q-Tel Invests In Data Analytics Company MapD”
2016-10-19 – The venture-capital arm of the Central Intelligence Agency, In-Q-Tel, said on Tuesday that it has invested in MapD Technologies Inc., a database and visualization startup.
Datanami, “The Here and Now of Big Geospatial Data”
2016-10-17 – No matter how sophisticated information technology gets – and who can deny that IT is evolving exceptionally fast these days – there’s nothing that can replicate the combination of two unique pieces of data: Time and place.
The Next Platform, “Ganging up Accelerators to Beat Scale Limits”
2016-10-11 – It is not news that offloading work from CPUs to GPUs can grant radical speedups, but what can come as a surprise is that scaling of these workloads doesn’t change just because they run faster.
IBM Cloud computing news, “The need for speed in IaaS platforms”
2016-10-11 – When you look at the rapidly evolving infrastructure as a service (IaaS) market, you might get the impression that it’s a race to the bottom with commodity hardware, inexpensive storage options, ongoing price cuts and the like.
RTInsights, “How GPU Computing Could Reinvent Real-Time Analytics”
2016-10-10 – The GPU has been around since “Space Invaders” — but it’s now capable of visualizing billions of data points in real time.
The Next Platform, “Accelerating Slow Databases That Wear People Down”
2016-10-05 – Todd Mostak, the creator of the MapD GPU-accelerated database and visualization system, made that database because he was a frustrated user of other database technologies, and as a user, he is adamant that accelerating databases and making visualization of queried data is about more than just being a speed freak.
PR Newswire, “MapD Named 2016 Startup of the Year”
2016-10-05 – Today, MapD received the Business Intelligence Group's BIG Award for Business and was named 2016 Startup of the Year.
datanami, “GPUs Seen Lifting SQL Analytic Constraints”
2016-10-04 – The availability of Nvidia K80s on AWS will be a turning point, MapD founder Todd Mostak wrote in a blog post last week.
Mapbox Blog, “Explore 1.2 billion taxi rides”
2016-09-30 – MapD, a GPU-powered database that uses Mapbox for its visualization layer, made it possible to quickly and easily interact with the data.
Business Wire, “AWS Announces Availability of P2 Instances for Amazon EC2”
2016-09-30 – New GPU instance type offers the most processing power available in the cloud for artificial intelligence, high-performance computing and big data processing
InfoWorld, “Faster with GPUs: 5 turbocharged databases”
2016-09-26 – Tired of slow joins and poky graph analytics? These database solutions use GPU acceleration for faster answers
NVIDIA Blog, “The Argument for Accelerated and Integrated Analytics”
2016-09-22 – The rise of modern business intelligence (BI) has seen the emergence of a number of component parts designed to support the different analytical functions necessary to deliver what enterprises require.
Business Insider, “I listened to 82 finance startup pitches — here's what I learned about where Wall Street is heading”
2016-09-22 – The common narrative when it comes to financial technology startups is that they pose an existential threat to established players.
Medium, “Startup Stories: From Scraping By On 10k From Parent Loans To Winning 100K: How Data Exploration Startup MapD Won Big”
2016-09-21 – The path to startup success is never dull and rarely ever easy.
CB Insights, “11 Startups To Watch At The Finovate Fall Conference In New York”
2016-09-07 – These are some of the companies you should be watching at FinovateFall based on CB Insights' predictive Mosaic scores.
Semiconductor Engineering, “MapD Makes GPUs First-Class Citizens”
2016-08-29 – A San Francisco-based startup has come up with a novel solution for solving the big data analytics challenge by leveraging GPUs.
PRNewswire, “MapD Adds Senior Executives for Engineering and Finance”
2016-08-16 – Addition of Bill Maimone and Alan Wong Round Out Senior Management Following $10 million Series A Round
MarksBlogg, “1.1 Billion Taxi Rides with MapD & 8 Nvidia Pascal Titan Xs”
2016-08-12 – In this blog post I'm going to see how much of an upgrade the new Pascal-based cards offer MapD when querying 1.1 billion taxi trips made in New York City over the course of six years.
insideBIGDATA, “The Hidden Cost of Latency in Analytical Applications”
2016-08-08 – Speed is increasingly defining the user experience from B2C to B2B.
MarksBlogg, “1.1 Billion Taxi Rides with MapD & AWS EC2”
2016-07-16 – The ability of MapD and Bitfusion to combine GPUs to create clusters of on-demand supercomputers, will have a profound impact on the size of the potential problems that can now be tackled.
Nvidia, “Ending Analysis Paralysis: NVIDIA and MapD Solve Massive Big Data Woes Across Industries”
2016-07-11 – MapD’s database intelligently partitions, compresses and caches data across all GPUs, providing users with up to 100x faster database queries
CRN, “The 10 Coolest Big Data Startups Of 2016 (So Far)”
2016-07-06 – MapD Technologies develops a big data analytics platform that the company says can query and visualize big data at a speed 100 times faster than other systems.
MarksBlogg, “1.1 Billion Taxi Rides with MapD & 4 Nvidia Titan Xs”
2016-07-05 – To top that off, I have yet to find another BI system capable of query speeds within an order of magnitude of what MapD has managed to deliver.
MarksBlogg, “1.1 Billion Taxi Rides with MapD & 8 Nvidia Tesla K80s”
2016-06-27 – For me personally, the future of BI reporting is GPU-based.
NextPlatform, “The Age of the GPU is Upon Us”
2016-05-31 – Having made the improbable jump from the game console to the supercomputer, GPUs are now invading the datacenter.
PRNewswire, “IBM Cloud First to Offer Latest NVIDIA GRID with Tesla M60 GPU, Speeding Up Virtual Desktop Applications”
2016-05-19 – By using IBM Cloud bare metal servers infused with NVIDIA GPU technology, MapD has created a super-high-speed database and visualization platform that filters and correlates multiple dimensions of multi-billion row datasets in milliseconds, without lag.
TheNewStack, “MapD Offers a Columnar Database System that Runs on GPUs”
2016-05-18 – San Francisco start-up MapD has released a database system, ParallelDB, built to run on GPUs (graphics processing units), which can be used to explore multi-billion row datasets quickly in milliseconds, according to the company.
TechTarget, “GPU database serves up analysis of tweets, other data feeds”
2016-05-11 – Mostak's team has fine-tuned the MapD platform by caching active data in GPU database memory, compiling queries on the fly using the Low-Level Virtual Machine (LLVM) framework and creating a system that can supportvectorised queries when possible.
Business Insider, “The weird way video games are paving the road to the future of technology”
2016-05-08 – MapD uses the ludicrous performance of these GPUs to analyze immense amounts of data
PRNewswire, “MapD Appoints Jonathan Symonds as Vice President of Marketing”
2016-05-03 – Company makes key marketing hires to accelerate growth following $10M Series A Round
PRNewswire, “MapD Named a "Cool Vendor" by Gartner for DBMS in 2016”
2016-04-27 – MapD selected as "Cool Vendor" for its interesting, new and innovative Database Management System
The Wall Street Journal, “MapD Locates $10 Million Series A for Faster Databases: Vanedge Capital led the round, which had participation from Verizon Ventures, Nvidia Corporation and GV.”
2016-03-30 – MapD uses [GPUs] to power SQL queries. The tool has a wide variety of applications for large sets of enterprise data. It has been used for social media analytics at companies such as Facebook, business intelligence at companies the likes of Verizon and recently has even been used by government agencies.
Verizon Ventures Blog, “Verizon Ventures Invests in MapD to Deliver Data Analytics at Light Speed”
2016-03-30 – It’s an all-too-common problem in today’s business landscape – companies are flooded with big data, but don’t have the tools and resources available to efficiently turn that data into insights.
Fortune, “Database Startup Snags $10 Million to Speed Analytics”
2016-03-30 – MapD, a startup that’s pressing graphics processors into service to speed up both number crunching and analytics of those numbers, now has $10 million in fresh funding to build up its engineering staff.
VentureBeat, “Nvidia backs GPU-powered data analytics tool MapD in $10 million round”
2016-03-30 – It turns out that [MapD’s] technology can even outperform in-memory databases, but not only that; the tool can then visualize results. Or it can just send query results to existing business-intelligence tools. Or it can work as a regular database. But no matter what companies choose to do with the technology, it is distinctive.
Bloomberg, “Database Startup MapD Raises $10 Million From Google, Nvidia”
2016-03-30 – MapD’s technology -- a database and a visual analytics system -- helps customers sift through and compare data quickly. The company uses what’s called graphics processing units, or GPUs, which are often used in computer gaming, and are faster than the central processing units traditionally used to power database systems.
Barron’s, “Database Startup MapD Brings to Life Dream of Gigantic GPU Clusters”
2016-03-30 – The innovation in MapD’s case is to use many, many GPUs, which makes it possible to store many tables in memory, which means scaling massively parallel collections of GPU cores will rise and rise...
Nvidia Blog, “MapD Lands $10M Investment, Launches Real-Time Database”
2016-03-30 – The MapD database uses GPUs to process SQL queries in parallel across nearly 40,000 cores per server, yielding massive speedups over leading in-memory databases. When paired with the MapD Immerse analytics front-end, the system delivers instant visual insights into datasets with billions of records.
The Next Platform, “MapD GPU Database Looks Forward To Heftier Iron”
2016-03-30 – The performance speedup that MapD has seen is impressive, and is akin to some of the boost that other parallel workloads in modeling, simulation, and machine learning have seen
InfoWorld, “MapD database rides GPUs for faster performance”
2016-03-30 – SQL queries are compiled to native GPU code via the LLVM compiler framework, but can also be compiled and run on each node's CPUs if needed. The latter can operate as a fallback if the data set for a query doesn't fit in GPU memory.
Silicon ANGLE, “MapD unveils a GPU-powered database for running complex visualizations”
2016-03-30 – The need for faster access to business intelligence is reshaping analytics environments all the way down to the hardware level...MapD Technologies Inc. now hopes to drive a similar shift over in the server layer with a newly launched database that uses GPUs instead of Intel Corp.’s more popular x86 chips to perform data visualization.
PRNewswire, “MapD Launches Lightning Fast GPU Database And Visual Analytics Platform; Lands $10M Series A Funding”
2016-03-30 – Solution harnesses Graphics Processing Units (GPUs) to query and visualize billions of records in milliseconds
Market Wired, “Seasoned Sales Leader Brock Alston Joins MapD as VP, Worldwide Sales”
2016-01-21 – Alston to Lead Go-to-Market Strategy for MapD's Big Data, Analytics and Visualization Platform
Fortune, “Nvidia must be stoked: This startup is taking graphics chips corporate”
2015-09-01 – With GPUs getting more memory, Mostak realized that the Intel and AMD part of the database can now take a backseat to the graphics processors because the GPUs finally have the memory capabilities to store the data as it’s being processed.
VentureBeat, “MapD closer to delivering ‘supercomputer in a box’”
2015-03-06 – MapD uses graphics processing units (GPUs) to crunch Big Data — the sort that usually only rooms full of servers are able to do, but “at a fraction of the price of what a big cluster [of servers] would cost, with much greater performance.”
Nvidia blogs, “MapD: Massive Throughput Database Queries with LLVM on GPUs”
2015-06-23 – Fast hardware is only half of the story, so at MapD we have invested heavily into optimizing our code such that a wide range of analytic workloads run optimally on GPUs. In particular, we have worked hard so that common SQL analytic operations, such as filtering (WHERE) and GROUP BY, run as fast as possible.
Data Informed, “Fast Database MapD Emerges from MIT Student Invention”
2013-04-22 – MapD uses graphics processing units (GPUs) to crunch Big Data — the sort that usually only rooms full of servers are able to do, but “at a fraction of the price of what a big cluster [of servers] would cost, with much greater performance.”
US News & World Report, “Until 2008, Trump Was a Big Democratic Donor”
2016-01-14 – Between 1989 and 2014, Trump donated a total of $1,219,950, according to data from the Center for Responsive Politics, obtained through the Sunlight Foundation. The video below, courtesy of MapD, a GPU-powered database and visualization platform for interactive data analytics, shows his ever-changing political allegiance.
eWeek, “IBM Puts Nvidia Tesla K80 GPU on SoftLayer Cloud”
2015-07-09 – Startup MapD has been using Tesla K80 accelerators on IBM Cloud for data and analytics. The solution enables multiple users to query and visualize multi-billion row data sets with latencies measured in milliseconds, achieving orders-of-magnitude increases in speed over other solutions.
Nvidia blogs, “We’re Helping Entrepreneurs Like You Get Money, Get GPUs, and Get Going – Here’s How”
2015-11-23 – In addition to the $100,000 investment we awarded, MapD has won early backing from Google Ventures and Vanedge Capital in Vancouver… Now MapD’s Mostak is readying the launch of his company’s first product early next year — an appliance that will allow companies to turn the terabytes of data they’ve gathered into instant visual intelligence.