Here at Kinetica, we are excited to partner with NVIDIA to drive innovation around the next big step in the evolution of big data–a trend that is garnering a huge amount of industry attention: GPU-accelerated analytics. Kinetica can perform brute-force processing on large, complex, and streaming datasets for true real-time analytics as a result of co-development efforts with NVIDIA. The result? Kinetica delivers 10 to 100x faster analytic performance utilizing a fraction of the hardware than legacy CPU-bound architectures.
As we enter the era of Industry 4.0, IoT, and a world where every facet of our lives become more interconnected, enterprises will become more reliant on highly performant and efficient platforms to keep pace with more evolved end user experiences. Innovations will drive adoption of architectures that have to deliver more than what traditional CPU-bound architectures are capable of. Supply chain use cases where interactive location-based analytics and machine learning have to come together, a place where many enterprises struggle today, can now be achieved in a much faster, efficient, and democratized fashion.
Industry 4.0 heralds a new era where manufacturing becomes intelligent, and every link in the supply chain talks to each other. There has been wide acceptance of 4 key design principles required to sustain this movement:
- Interoperability: The ability of machines, devices, sensors, and people to connect and communicate with each other via the Internet of Things (IoT) or the Internet of People (IoP).
- Information transparency: The ability of information systems to create a virtual copy of the physical world by enriching digital plant models with sensor data. This requires the aggregation of raw sensor data to higher-value context information.
- Technical assistance: First, the ability of assistance systems to support humans by aggregating and visualizing information comprehensibly for making informed decisions and solving urgent problems on short notice. Second, the ability of cyber physical systems to physically support humans by conducting a range of tasks that are unpleasant, too exhausting, or unsafe for their human co-workers.
- Decentralized decisions: The ability of cyber physical systems to make decisions and to perform their tasks as autonomously as possible. Only in the case of exceptions, interferences, or conflicting goals, are tasks delegated to a higher level.
To deliver on these core tenets, customers have to be able to harness next-generation architectures without overhauling their internal skill sets. The ability to simplify streaming use cases with Kinetica and NVIDIA will enable customers to efficiently deliver against these challenges and gain competitive advantage over organizations who have not connected GPU-accelerated platforms to their data sources.
NVIDIA NVLink is a high-bandwidth, energy-efficient interconnect that enables ultra-fast communication between the CPU and GPU, and between GPUs. Kinetica utilizes an MPP architecture capable of immense scale across multiple, high-density nodes to deliver unrivaled performance. In addition, Kinetica’s orchestration layer can perform compute-to-grid analytics with GPU-accelerated libraries, non GPU-accelerated libraries, and/or custom-built logic.
Customers want their business teams to have access to data science algorithms without moving data, and to have the ability to run simulations (Monte Carlo), risk modeling, trade risk, and advanced calculations (Linear Interpolation) against millions of data points in an easy, repeatable, performant way. With Kinetica and NVIDIA, customers can now converge IoT data, business intelligence, deep learning, and machine learning workloads while democratizing the data science process.
The NVIDIA / Kinetica partnership is already having a dramatic impact across a wide variety of industries and applications, even beyond those enabled by Internet 4.0, including driverless cars, smart factories, preventive maintenance, predictive healthcare, real-time fraud detection, and risk analysis. Simply put, the integration of NVIDIA GPUs within Kinetica’s highly scalable, MPP, in-memory database is unleashing the power of accelerated analytics to transform data-driven businesses into AI enterprises.
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