Wednesday, September 27th 2023

AMD Unveils Alveo UL3524 Purpose-Built, FPGA-Based Accelerator

AMD today announced the AMD Alveo UL3524 accelerator card, a new fintech accelerator designed for ultra-low latency electronic trading applications. Already deployed by leading trading firms and enabling multiple solution partner offerings, the Alveo UL3524 provides proprietary traders, market makers, hedge funds, brokerages, and exchanges with a state-of-the-art FPGA platform for electronic trading at nanosecond (ns) speed.

The Alveo UL3524 delivers a 7X latency improvement over prior generation FPGA technology, achieving less than 3ns FPGA transceiver latency for accelerated trade execution. Powered by a custom 16 nm Virtex UltraScale + FPGA, it features a novel transceiver architecture with hardened, optimized network connectivity cores to achieve breakthrough performance. By combining hardware flexibility with ultra-low latency networking on a production platform, the Alveo UL3524 enables faster design closure and deployment compared to traditional FPGA alternatives.
"In ultra-low latency trading, a nanosecond can determine the difference between a profitable or losing trade," said Hamid Salehi, director of product marketing at AMD. "The Alveo UL3524 accelerator card is powered by the lowest latency FPGA transceiver from AMD—purpose-built to give our fintech customers an unprecedented competitive advantage in financial markets."

Hardware Flexibility and AI-Enabled Trading Strategies
Featuring 64 ultra-low latency transceivers, 780K LUTs of FPGA fabric, and 1,680 DSP slices of compute, the Alveo UL3254 is built to accelerate custom trading algorithms in hardware, where traders can tailor their design to evolving strategies and market conditions. Supported by traditional FPGA flows using Vivado Design Suite, the product comes with a suite of reference designs and performance benchmarks that allow FPGA designers to quickly explore key metrics and develop custom trading strategies to specification, backed by global support from AMD domain experts.

To simplify the increasing adoption of AI in the algorithmic trading market, AMD is providing developers with the open-sourced and community-supported FINN development framework. By using PyTorch and neural network quantization techniques, the FINN project enables developers to reduce the size of the AI models while retaining accuracy, compiling to hardware IP, and integrating the network model into the algorithm's datapath for low latency performance. As an open-source initiative, the solution gives developers flexibility and accessibility to the latest advancements as the projects evolve.

Enabling a Growing Ecosystem of Ultra-Low Latency Fintech Solutions
The Alveo UL3524 and purpose-built FPGA technology are enabling strategic partners to build custom solutions and infrastructure for the fintech market. Currently available partner solutions include offerings from Alpha Data, Exegy, and Hypertec.

The AMD Virtex UltraScale+ VU2P FPGA powering the Alveo UL3524 accelerator card is enabling ultra-low latency appliances from Alpha Data.

"The new Virtex UltraScale+ FPGA from AMD brings a step change to ultra-low latency trading and networking," said David Miller, managing director of Alpha Data. "We've developed the ADA-R9100 rack-mount appliance which allows customers to easily access the full potential of the new AMD FPGA device."

Exegy, a provider of end-to-end, front-office trading solutions, is supporting the Alveo UL3524 card with its nxFramework, a software and hardware development environment tailored for creating and maintaining ultra-low latency FPGA applications within the financial industry.

"By combining the pioneering ultra-low latency FPGA technology from AMD with Exegy's expertise in capital markets, we're able to deliver a comprehensive solution that addresses the ever-increasing optimization needed to build the trading infrastructure of tomorrow," said Olivier Cousin, director of FPGA solutions at Exegy.

Hypertec has optimized its ORION HF X410R-G6 High Frequency Server for the Alveo UL3524 with a custom cooling system to deploy in a 1U server form factor.
"The engineers at Hypertec specifically designed the HF X410R-G6 to extract the best out of the capabilities and speed of the Alveo UL3524 platform, catering our solution to the most demanding low-latency tasks," said David Lim, director of product marketing, Hypertec.

The AMD Alveo UL3524 accelerator card is currently in production and shipping to global financial services customers.
Source: Xilinx
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7 Comments on AMD Unveils Alveo UL3524 Purpose-Built, FPGA-Based Accelerator

#1
Wirko
More better HFT? The world is three inches closer to hell once more.
Posted on Reply
#2
Blurpy
So much Hype around this
Posted on Reply
#3
Tropick
WirkoMore better HFT? The world is three inches closer to hell once more.
They should throw in a free 8ball of coke when you purchase the card to enable the full day trading experience
Posted on Reply
#4
Ferrum Master
WirkoMore better HFT? The world is three inches closer to hell once more.
But.... that's the plan.

But tbh bragging about latency improvement ain't that bad... that the area they suck.
Posted on Reply
#5
dragontamer5788
This is very much outside anything I actually do, but my understanding is that Alveo FPGAs are more programmed rather than Verilog-designed. Yes, there's a degree of flexible LUTs / routing so its an FPGA, but the DSPs are in some kind of VLIW + SIMD architecture internally, and that runs of course an instruction set akin to a digital-signal-processor (or perhaps a Terrascale GPU from a decade ago).

Its a very odd arrangement of compute, but obviously has its customers.
Posted on Reply
#6
thesmokingman
When you need to high frequency trade... look no further for the best front running!
Posted on Reply
#7
stimpy88
What, no "A.I." or "cognitive" tech in it? Ah, so no marketing BS in this market I see. The day "A.I." or "cognitive" are used with such a product, is they day I believe those technologies are real.
Posted on Reply
Dec 22nd, 2024 02:03 EST change timezone

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