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Myrtle.ai Halves Latency in Financial Machine Learning Inference Benchmark Record with VOLLO
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29 Apr, 2026, 15:05 CST

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CAMBRIDGE, England, April 29, 2026 /PRNewswire/ -- myrtle.ai, a recognized leader in accelerating machine learning inference, today announced that a stack featuring its VOLLO® product has recently been audited by STAC®, a leading benchmark authority for the finance industry.[1] The results, unveiled at the STAC Summit in London today, clearly demonstrate the latency benefits of an FPGA-based solution for ML inference in financial trading and related applications.

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Myrtle.ai Halves Latency in Financial Machine Learning Inference Benchmark Record with VOLLO
Myrtle.ai Halves Latency in Financial Machine Learning Inference Benchmark Record with VOLLO

STAC-ML (Markets) Inference is the technology benchmark standard for solutions that may be used to run inference on real-time market data. Designed by quants and technologists from some of the world's leading financial firms, STAC-ML Markets (Inference) reports the performance, resource efficiency, and quality of any technology stack capable of performing inference using the provided models.

VOLLO achieved latencies as low as 2 microseconds (99th percentile) while also exhibiting excellent results in throughput and efficiency. Across all three benchmark models, VOLLO inferred in lower latency (99th percentile) than all previously audited systems, halving its previous record. Such low, deterministic latency enables users to make more intelligent decisions using more complex models faster than in the past, giving them a competitive advantage in trading, risk analysis, quotes and many other trading-related activities.

With hundreds of thousands of hours of production trading under its belt, VOLLO is generating alpha for many of the world's leading trading firms today. Those firms have developed and trained a wide range of models in standard ML tool flows before compiling them into VOLLO and then running them on their choice of FPGA-based hardware platform.

In the system under test, VOLLO ran on the standard form factor FBAP4@VP18-2L0S PCIe accelerator card from Silicom, containing an AMD Versal™ Premium series VP1802 Adaptive SoC and installed in a Supermicro AS -2015CS-TNR server. The AMD Versal Premium Series Adaptive SoC provides PCIe Gen5x8 and more than 3.3M programmable LUTs, making it well suited to low latency inference applications.

"Since VOLLO first exploited the full potential of FPGAs in this STAC benchmark in 2023, we have worked with our customers to further reduce latencies, expand the variety and size of models that VOLLO can run, and grow the range of platforms it can run on," said Peter Baldwin, CEO of myrtle.ai.  "We're excited to work with AMD, Silicom and Supermicro on this benchmark, to demonstrate how our combined technologies can enable ultra-low latency AI inference in quant trading."

"The future of financial markets will be shaped by AI systems that can interpret data and act on it in near real time," said Girish Malipeddi, director for Data Center FPGA business, AMD. "With AMD Versal™ Premium series adaptive SoCs at the foundation, myrtle.ai's VOLLO demonstrates how advanced, low-latency inference can help unlock a new generation of intelligent trading infrastructure."

"Supermicro continues to address a wide range of markets with our AMD systems, which were used for this STAC-ML benchmark," said Michael McNerney, Senior Vice President Marketing and Network Security, Supermicro. "Our servers address the most challenging workloads in the financial services industry, and together with partners, we are able to deliver top-end performance with very low latencies for machine learning workloads."

Anders Poulsen, VP Solutions at Silicom Denmark, said: "We're pleased that myrtle.ai selected Silicom's Artena accelerator card, based on AMD Versal Premium, for these tests. Built around one of the largest FPGAs in a PCIe form factor, Artena is an ideal platform for VOLLO. Together, VOLLO and our low-latency hardware deliver deterministic, microsecond-level inference for demanding trading workloads."

ML developers can evaluate today how their models could perform on VOLLO, without the need for any FPGA tools or expertise. For more details go to vollo.myrtle.ai or contact myrtle.ai today at [email protected].

The full benchmark results are available in the STAC Report (SUT ID MRTL260323) at http://www.STACresearch.com/MRTL260323.

About myrtle.ai

Myrtle.ai is an AI/ML software company that delivers world-class inference accelerators on FPGA-based platforms from all the leading FPGA suppliers. With broad neural network expertise, myrtle.ai has delivered accelerators for applications including fintech, wireless telecoms, LLMs, speech processing, and recommendation.

VOLLO, VOLLO Accelerator and the VOLLO logo are registered trademarks of myrtle.ai.

"STAC" and all STAC names are trademarks or registered trademarks of the Strategic Technology Analysis Center, LLC. AMD, the AMD logo, Versal, and combinations thereof are trademarks of Advanced Micro Devices, Inc. 

[1] www.STACresearch.com/MRTL260323

SOURCE Myrtle.ai

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