About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

NovaSparks’ STAC-M1 Benchmark Highlights Determinism Under Load

Subscribe to our newsletter

A just released STAC Report covering the performance of NovaSparks’ FPGA market data platform highlights not just its processing latency but also the deterministic nature of that latency under different data loads.

The STAC-M1 benchmark (as defined by financial markets participants and administered by the Securities Technology Analysis Center) measures the performance of direct data feed processing solutions according to a number of different criteria, including end-to-end latency and throughput.

The NovaSparks solution uses only FPGA microprocessors in its architecture, in contrast to offerings that augment mainstream x86 processors with FPGA acceleration of certain functions. As such, the company claims its platform is less prone to latency variance – or jitter – compared to its competitors.

The predictable – or deterministic – nature of the NovaSparks platform was borne out by the benchmark tests conducted by STAC, which simulated a Nasdaq TotalView ITCH feed being received at 2x and 20x a typical data rate at market open and close.

According to STAC: “During replay at 20 times recorded market data volumes, the NovaSparks solution demonstrated mean latency of just 1.4 microseconds, along with 99.9th percentile latency of just 2.8 microseconds. Jitter (standard deviation) was just 0.12 microseconds at 2x market rate and 0.15 microseconds at 20x market rate.” See this chart:

 

While for many the push to reduce latency further is not as big a focus as it once was, maintaining deterministic latency is still important for many trading strategies. Keeping latency constant under extreme market conditions has historically been a challenge, and its one that NovaSparks is looking to solve with its FPGA platform.

“Deterministic processing of market data at ultra-low latency rates is a breakthrough for an industry that is constantly re-assessing their ability to trade across all market conditions,” says Michal Sanak, CIO at proprietary trading firm RSJ.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Reviewing the Latency Landscape and the Next Generation of Ultra-Low Latency Infrastructure

Date: 17 September 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Ultra-low latency is no longer the preserve of a handful of proprietary trading firms. As new asset classes electronify, data volumes surge, and regulatory expectations around execution quality and resilience tighten, the performance demands on trading infrastructure are broadening...

BLOG

Watching the Future: The Top 10 Surveillance and Compliance Challenges in Prediction Markets

By Joe Schifano, Global Head of Regulatory Affairs, Eventus. Prediction markets are quickly becoming the next frontier of finance – a new class of markets where people trade on what they believe will happen next. From election results to interest rate fluctuations, these platforms turn collective judgment into tradable data. But as prediction markets move...

EVENT

TradingTech Summit New York

Our TradingTech Summit in New York is aimed at senior-level decision makers in trading technology, electronic execution, trading architecture and offers a day packed with insight from practitioners and from innovative suppliers happy to share their experiences in dealing with the enterprise challenges facing our marketplace.

GUIDE

ESG Data Handbook 2022

The ESG landscape is changing faster than anyone could have imagined even five years ago. With tens of trillions of dollars expected to have been committed to sustainable assets by the end of the decade, it’s never been more important for financial institutions of all sizes to stay abreast of changes in the ESG data...