STAC Summit, 31 May 2023, NYC

• Bishop Brock, Head of Research, Securities Technology Analysis Center
• Peter Nabicht, President, Securities Technology Analysis Center

Bishop and Peter will present the latest STAC Benchmark Council activities in storage and compute critical workloads, including STAC-M3 (the full stack needed for enterprise tick analytics) and STAC-A3 (strategy backtesting).

• Matthew Nassr, Global Data Engineering Lead, Optiver
• Michael Rothenberg, Global UDS Business Development, Financial Trading & Energy, Dell Technologies
• Keith Miller, VP Technical Sales, Services and Support, DDN
• Joel Kaufman, Senior Technical Marketing Manager, WEKA
• Rob Glanzman, Global Strategic Alliances Principal Architect, Financial Services, Pure Storage

Trading and investment firms must gain an advantage over the vast and ever-growing data they process, store, and analyze. Object stores, originally used for low-cost snapshots and archives, now bring space and cost savings to mission-critical applications. Could they be the lever that financial firms need? For object stores to provide leverage, everyone from storage architects to software developers needs to understand them. Our panel of experts will discuss important aspects, including use cases the performance is suitable for, how get/pull differs from read/write, integrating existing storage solutions and analytic stacks, and how moving this cloud-native technology on-prem impacts hybrid systems. Join us to explore how object stores can help you shoulder the weight of data. To kick off, some of the panelists provided a short presentation:

• Bishop Brock, Head of Research, Securities Technology Analysis Center
• Peter Nabicht, President, Securities Technology Analysis Center

Peter and Bishop will discuss the latest research and STAC Benchmark Council activities related to machine learning, including updates on inference and training workloads. Peter will also present results from recent STAC-ML audits.

• John Chan, Director of Technology – AI/ML, Raymond James Financial
• Dr. Prabhanjan (Anju) Kambadur, Head of AI Engineering, Bloomberg
• Hunter Almgren, Distinguished Technologist, Hewlett Packard Enterprise
• Ioana Boier, Senior Principal Applied Researcher and Solutions Architect, NVIDIA

GPT-4 and other generative AI could be creating a watershed moment for the software development life cycle. In everything from Python to C++ and even VHDL/FPGA, large language models (LLMs) are starting to help with code generation, reviews, documentation, and testing—including creating data sets to probe the edges of algorithms. No one wants to be left behind, but adoption requires answering critical questions. Will LLMs provide great leaps in productivity or only incremental assistance? Can they turn English into an effective programming language (even enabling someone with no coding experience to develop software)? Do we risk automating the errors and poor code too often found on Stack Overflow and developer blogs? Can we benefit without leaking our trade secrets or violating someone else's copyrights? Our panel of experts will examine the extent to which financial firms and their engineers can leverage LLMs to boost productivity, improve software quality, and accelerate time to market. Along the way, they'll consider security and bug risks, as well as the guardrails needed to keep our software—and markets—safe. Join them to discuss how to benefit from the bleeding edge. To kick off, some of the panelists provided a short presentation:

• Peter Nabicht, President, Securities Technology Analysis Center

Peter will discuss the latest STAC Benchmark Council updates on defining cloud communication benchmarks for on-prem-to-cloud and cloud-to-cloud communications

• Shaun Laurens, Head of Java, US, Adaptive

Low and consistent messaging latency are fundamental requirements for trading infrastructure. Kernel bypass technologies and UDP—both often discussed at STAC events—are dominant tools in on-prem, low-latency messaging but are largely absent in public clouds. Can trading workloads migrate to the cloud without them and still be successful? Shaun thinks success is possible if you embrace different techniques and leave the "lift-and-shift" approach behind. He'll examine common issues when communicating between processes and containers over a software-defined IP network. He'll also cover emerging patterns that help overcome the challenges, including kernel bypass in the cloud, IPC, and simulated multicast. Along the way, he'll address how developers can modify software to take advantage of these patterns and achieve fanout. Be sure to bring your questions for Shaun as he explores if the cloud can support your messaging needs.

• Nikhil Singhvi, Managing Director of Core Trading Technology, Credit Suisse
• Cam Colella, Head of Technology, Flow Traders US
• Michael Galime, Director - Finance and Capital Markets, Keysight Technologies

As we've discussed at past STAC events, exchanges and central service providers are moving important functions into the cloud. Matching in traditional asset classes may take a while to migrate, but the logic for many surrounding functions is compelling. Trading firms will either want or need to follow suit, which means architecting for cloud has become critical. This raises many questions for an industry that has relied mostly on on-premises solutions. Which functions are likely to become most common in the cloud, over what time horizon? What kind of throughput, latency, and consistency can the cloud provide? How will the technologies that financial firms have come to rely on be adapted to the cloud? How should architects handle infrastructure decisions such as whether to go hybrid cloud or multi-cloud? Join our panelists as they dive into these questions and yours.

• Kevin Stanton, Sr. Principal Engineer, Intel Corporation

Precise, synchronized clocks are necessary to monitor, manage, and continuously improve low-latency systems. Network synchronization for delivering accurate, reliable time from an authority to a system has been an important topic of discussion and learning at previous STAC events. But trading software requires synchronization all the way to each CPU core. These remaining centimeters have always been a weak link due to the non-determinism in relying on software for time sync. Kevin will present how to get the most from PCIe Precision Time Measurement (PTM), a hardware-based solution that transfers time across multiple components with independent local time clocks. He'll cover how PTM enables time coordination, demonstrate its efficacy, and explain how you get started. Bring your questions and join Kevin as he explores what to do when the "last mile" is measured in centimeters.

• Peter Nabicht, President, Securities Technology Analysis Center

Peter will discuss updates from the FPGA special interest group and the latest results and STAC Benchmark Council activities related to low-latency/high-throughput realtime workloads.

• Dr. David Snowdon, Director of Engineering, Arista Networks

Migration to 25G, 40G, and 100G Ethernet is in full swing among enterprises and cloud providers, but exchange connections and trading infrastructures have resolutely remained at or below a 10G ceiling. It is tempting to believe this will always be so. But ever-increasing data rates and the need for larger data sets create mounting pressure for more bandwidth. Will trading be able to resist the pressure forever? Dave will explore whether the industry can change to 25G, along with several related questions. What impact will 25G have on low-latency infrastructure, not to mention timestamping, data capture, and operational support? Will firms use forward error correction, given the latency hit, and if not, how can they manage the data risk? How will more bandwidth impact market microstructure, and will it enable more insight into exchange behaviors? Join Dave as he looks at a possible future of trading networks.

• Michael Gorbovitski, Executive Director, Morgan Stanley
• Matt Certosimo, Data Center FPGA Field Application Engineer, AMD
• Adam Sherer, Verification Technology Executive, Cadence Design Systems

It's no secret that FPGAs are a favorite component for ultra-low latency system engineers. Firms can gain a significant edge by placing relatively simple trading strategies in an FPGA to avoid user space entirely. But what role can FPGAs play in more complex, compute-hungry strategies? Can FPGAs combine with other processors in quant-based trades or critical pricing algorithms? For that matter, does FPGA have a home outside real-time decision-making, such as in research infrastructures? Join our panelists as they discuss these questions and yours on the future of FPGAs in capital markets. To kick off, some of the panelists provided a short presentation: