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Learn About the New Block Floating Point Arithmetic Unit for Processing AI/ML Workloads in Speedster7t FPGA

Block floating point (BFP) is a hybrid of floating-point and fixed-point arithmetic where a block of data is assigned a common exponent. Learn about the only FPGA with machine learning processors that can deliver native BFP capabilities with higher performance and lower power consumption compared to traditional FPGA DSP blocks. 

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Learn How FPGA-based PCIe Cards Can Accelerate Your Applications

In this webinar, you will learn how to leverage FPGA-based PCIe accelerator cards to achieve 10-100x increase in performance vs. CPU-only based solutions for compute, network, storage and sensor processing applications.

See how off-the-shelf FPGA-based accelerator cards can deliver increased efficiency and operational agility while reducing your time to market.

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Accelerate Data Processing Algorithms using FPGAs with 2D Network-on-Chip

This novel architecture has hundreds of NoC-access-points located throughout the FPGA core that can access off-chip memories and any of the high-speed PCI Express ports. This family of FPGAs also include specialized modes for the high-speed 400G Ethernet ports.

In addition, you will see how data can be streamed across the FPGA fabric using 512 Gbps NoC channels located throughout the FPGA processing array.

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Embedded FPGA and FPGA: The Fabric for Optimized Machine Learning

Embedded FPGAs (eFPGAs) bring the power and flexibility of programmable logic to ASICs and SoCs. With eFPGAs, machine learning (ML) can be integrated in new form-factors such as mobile edge compute, IoT aggregation and SmartNIC.