STAC Summit, 30 May 2024, Chicago

• Jack Gidding, CEO, Strategic Technology Analysis Center

Jack will provide a preliminary look into STAC-AI™, an LLM benchmark suite guided by the priorities of financial firms, which measures a full solution stack -- from the model to the metal™

• Prabhu Ramamoorthy, Global Partner Success Manager, NVIDIA - Financial Services and Technology Team (sponsored by Supermicro)

Financial firms rely upon HPC architectures to develop and backtest trading strategies, calibrate models, and calculate risk. Fast time to market requires fast compute. So does GenAI, which many firms see as a powerful new way to inform strategies or risk management from unstructured data. In this talk, Prabhu will argue that a single architecture can satisfy both financial HPC and GenAI—as long as it has certain key properties like seamless CPU-GPU integration. As evidence, Prabhu will present use cases from financial firms and ISVs like Murex and KX, explaining how they benefit from massive compute, unified memory, and low-latency interconnects for heterogeneous compute.

• Jack Gidding, CEO, Strategic Technology Analysis Center

Jack will present the latest Council activities and benchmark results involving derivatives risk computation.

• Jack Gidding, CEO, Strategic Technology Analysis Center

Jack will present the latest Council activities and benchmark results for deep time-series analytics.

• Jerry Nelligan, CTO, XR Trading
• Kevin Darby, VP of Execution Tech, CQG Inc
• Attila Narin, Vice President of Cloud Engineering, Oracle
• Brian Evans, Director, Americas Pre-Sales, DDN
• Michael McGuirk, Sr Manager, Data Center Marketing, AMD

Banks and hedge funds require more compute, storage, and networking to meet increasing demands for trading and risk analytics. Data volumes continue to balloon, regulations require more simulations, and new market opportunities require new analytics. However, generative AI and cloud have famously become "gravity wells" for the IT industry, driving its product roadmaps. On the one hand, this may increase the options available for financial HPC and data-intensive workloads, driving down long-term costs. On the other hand, AI and hyperscaler architectures can differ in important ways from those of today's trading and risk analytics, which presents challenges. To what extent can the finance industry benefit from the new products coming forth? How much longevity is left in existing approaches? Are there opportunities (or even imperatives) for trading and investment firms to rethink how they design their applications and infrastructure?

• Jack Gidding, CEO, Strategic Technology Analysis Center

Jack will discuss the latest Council activities and test results relating to 1) low-latency LSTM inference on market data and 2) network stacks in the cloud and on the ground.

• Mike Schonberg, Director of Market Data Technology, Quincy Data

Building a time-synchronization network spanning multiple data centers within a metropolitan area is a formidable challenge, particularly when the requirements include fault tolerance, nanosecond accuracy, and traceability to UTC(NIST). Quincy Data undertook this challenge, using White Rabbit in Chicago and New Jersey to synchronize across the major trading venues and using GNSS to connect these metros into a single clock domain. Come to hear Mike explain some of the problems Quincy encountered in design and implementation and how they overcame them.

• Ken Willis, Application Engineering Group Director, Cadence

Supporting 25G Ethernet can reduce the latency of FPGA or ASIC algorithms--but only if it is implemented well. Signal integrity, power, and thermal challenges exist all the way from the 25G IP, through the package, and across the PCB. In this talk, Ken will explore these challenges and present methods to analyze and resolve them so that you can achieve cool speed with 25G.

• Eric Powers, Director, Head of High Performance Architectures Infrastructure, Citi
• Daniel Wisehart, Head of Hardware Development, Cubist Systematic Strategies
• Matt Certosimo, Data Center FPGA Field Application Engineer, AMD
• Patrick Egan, Head of Business Development, Shengli Technologies

To stay in the game, trading firms must manage ever-growing data rates and keep their architectures competitive, whether it’s making software faster or hardware smarter. But mounting requirements for regulation, compliance, and cyber are straining resources. Meanwhile, finding well-trained talent is only getting harder. What are the best strategies to navigate these constraints? What are the best buy/hold/sell strategies for technologies across the spectrum, from FPGA and ASIC to private clouds? Where does it make sense to buy third-party logic today? Our panel of experts will weigh in.