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“Multi-cloud” means multiple public clouds. A company that uses a multi-cloud deployment incorporates multiple public clouds from more than one cloud provider. Instead of a business using one vendor for cloud hosting, storage, and the full application stack, in a multi-cloud configuration they use several¹ .

Multi-cloud deployments have several…

In this tutorial, we will lay out the absolute easiest way to begin using FPGA resources in Kubernetes clusters. To really simplify things, we will describe the process for enabling FPGAs in terms of the Rancher user interface. The Rancher UI is simply a client to the Rancher RESTful APIs…

Customized compute acceleration in the datacenter is key to the wider roll-out of applications based on deep neural network (DNN) inference.

A great article by Xilinx Research Labs shows how to maximize the performance and scalability of FPGA-based pipeline dataflow DNN inference accelerators (DFAs) automatically on computing infrastructures consisting of…

AMD’s (AMD) $35 billion deal to acquire Xilinx (XLNX) has been recently approved by shareholders of both chipmakers. However there are several cases in the domain of deep learning that GPUs are considered more powerful than FPGAs. Then, why AMD decided to acquire Xilinx for $35 billion instead of further…

FPGAs have been emerged as a high-performance computing platform that can meet the demanding AI requirements in terms of throughput, latency and energy-efficiency. FPGA vendors like Xilinx, Intel and Achronix have developed great FPGA platforms for data center and edge applications.

However a main challenge on the domain of AI/ML…

MindsDB is an open-source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning models using SQL queries. For more flexibility MindsDB has developed the Lightwood framework. Lightwood has one main class, the Predictor, which is a modular construct that you can train…

Deep neural networks, and AI in general, can offer tremendous advantages in many sectors like healthcare, finance, logistics, marketing, and research. However, all the AI models like deep learning, reinforcement learning, etc. are computationally intensive and require enormously powerful processing platforms. …

Automatic Object Detection using machine learning is one of the most promising technologies in the domain of video classification and detection. Object detection in video is computationally intensive task that requires huge amount of processing power. …

On June 1, 2015 Intel and Altera announced , that they had entered into a definitive agreement under which Intel would acquire Altera for $16.7 billions. That was a major milestone for the FPGA community as Xilinx and Altera were the main FPGA vendors.

After the official announcement of AMD…

Evaluating the best hardware platform for your deep learning application can sometimes be challenging. Also, the marketing numbers provided by several companies sometimes can be misleading as they refer to specialized benchmarks. MLPerf’s mission is to build fair and useful benchmarks for measuring training and inference performance of ML hardware…

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