CONTACT MLE
We are glad that you preferred to contact us. Please fill our short form and one of our friendly team members will contact you back.


    NPAP-10G Remote Eval.NPAP-25G Remote Eval.


    X
    CONTACT MLE

    Shift-Left Your FPGA Design Projects

    Shift-Left Your FPGA Design Projects

    Summary

    FPGA Full System Stacks comprising off-the-shelf FPGA System-on-Modules (SoM) plus pre-validated FPGA IP Cores and subsystems can greatly accelerate the time-to-market of your FPGA design project. Advantages of FPGA Full System Stacks include:

    1. FPGA developers can rely on a tested and verified subsystem implementation. The concept of re-use increases design productivity while sharing the FPGA subsystem development costs and risks over many users.
    2. Pre-validated FPGA IP-Cores and subsystems make clever use of the different FPGA resources to realize a cost/performance optimized domain-specific architecture.
    3. Software is included in the form of kernel space device drivers, user-space programmer APIs, and sometimes even complete OS images, all nicely tuned for guaranteeing the overall system’s reliability and performance.

    FPGA Full System Stacks from MLE are integrated with select FPGA SoMs from Trenz Electronics and are focused on applications such as:

    • Realiable, Low-Latency, High-Throughput Network Transports
    • High-Speed Data Acquisition
    • Augmented Stereo Computer Vision
    • High-Speed Data Record & Replay

    We describe a design methodology using FPGA Full System Stacks and share our experiences from real customer designs.

    Deterministic Networking with TSN-10/25/50/100G

    Deterministic Networking with TSN-10/25/50/100G

    Growing Demand for Deterministic Networking

    We all observe a growing need to connect computers with each other with shorter delays (i.e. lower latencies) and higher bandwidth, in particular for High-Performance Computing (HPC) in the data center and in embedded systems such as advanced industrial robotics or autonomous vehicles, requiring the so-called deterministic networking. Processing of TCP/IP based network protocols at speeds of 10 Gbps and beyond demand kernel bypass solutions (such as Intel’s DPDK or Solarflare’s/Xilinx’ Onload or Mellanox/NVida VMA) and/or so-called TOEs (TCP Offload Engines). 

    Domain-Specific Architectures (DSA) use so-called heterogeneous computing elements, also known as Cores with the objective to put the compute burden where it belongs. This is a well established approach going back to the early days when an x86 CPU was partnered with an x87 for better floating-point processing. Today, it is common to deploy various flavors of Cores, for example:

    • DSP Cores for digital signal processing in telecommunications
    • Shader Cores optimized for image processing, as they can be found in modern Graphics Processing Units (GPU) 
    • Tensor Processing Units (TPU) Cores which are optimized for Artificial Intelligence and Deep Learning

    This is because such (special purpose) fixed-function or programmable function accelerator Cores are optimized for a particular domain and, when properly used, not only take processing load off the (general purpose) CPU but also deliver better overall performance (which is data processed per time) and better efficiency (which is performance per Watt).

    Over the following pages we will make a case for processing TCP/IP over TSN over 10/25/50/100 Gigabit Ethernet on dedicated Cores which has significant advantages in particular for real-time Ethernet and Deterministic Networking. These so-called TCP-TSN-Cores can be integrated either in FPGAs or in SoCs (ASIC and ASSP). As we will show, TCP-TSN-Cores are more than just a TOE – the commonly used approach for network protocol acceleration. By running the entire network protocol stack from OSI Layer 2 to at least Layer 4 in a dedicated integrated circuit – a so-called Full Accelerator – we can remove (general purpose) CPUs entirely from the datapath. 

    Hence, TCP-TSN-Cores can deliver very low bounded and deterministic latency with predictable scalability needed for 10/25/50/100 Gigabit Deterministic Networking.