
Myrtle.ai MAU Accelerator for AI Financial Trading Models
REFERENCE DESIGN MAU Accelerator for AI Financial Trading Models Ultra-low Latency, High Throughput Machine Learning Inference Well suited to a range of applications in financial
The GROVF RDMA IP core and host drivers provide RDMA over Converged Ethernet (RoCE v2) system implementation and integration with standard Verbs API. The RDMA IP is delivered with a reference design that includes the IP subsystem itself, the 100G MAC IP subsystem, the DMA subsystem, host drivers, and example application on software. The system drivers are integrated with OFED standard Verbs API and are compatible with well-known RNIC cards and software. The IP core also provides a low-latency FPGA implementation of RoCE v2 at 100 Gbps throughput.
The solution is a soft IP implementing RDMA over Converged Ethernet protocol. It consists of FPGA IP integrated with MAC and DMA, plus the host CPU drivers and is compatible with a variety of BittWare’s FPGA cards. The 200Gbps IP is compatible with BittWare’s IA-440i Agilex 7 I-Series FPGA card, and the 100Gbps IP is compatible with BittWare’s IA-840f and IA-420f Agilex 7 F-series cards and XUP-VV8 and XUP-P3R UltraScale+ FPGA cards. The solution complies with Channel Adapter and RoCE v2 requirements as stated in the IB specification. The diagram on page 1 shows a simplistic architectural overview of the system. The data plane and reliable communication is hardware offloaded and the implementation does not include CPU cores in the FPGA.
The reference example consists of three parts:
Device | LUTs | On-Chip Memory |
---|---|---|
UltraScale+ VU9P | 170K | 6Mb |
Agilex 7 AGF014 | 170K | 6Mb |
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REFERENCE DESIGN MAU Accelerator for AI Financial Trading Models Ultra-low Latency, High Throughput Machine Learning Inference Well suited to a range of applications in financial
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