Global STAC Live, Spring 2020

• David Rukshin, CTO, WorldQuant
• Caius Howcroft, Head of Infrastructure and Data Platform, Tradeweb
• Michael Recce, Chief Data Scientist, Neuberger Berman

The COVID-19 crisis has changed the game for trading and investment strategists as well as risk managers. It has upended the economy, precipitated unprecedented fiscal and monetary intervention, and introduced or exacerbated political risks. Markets have responded with both the biggest bear and bull markets in decades, the VIX soaring from 17 to 80 in less than a month, oil futures going negative, and many other black swans. Meanwhile, the volumes of data to be analyzed have grown dramatically, presenting computing challenges at precisely the time when analysts need faster answers. How have these shocks changed the demands for analytics and the systems that produce them, from strategy research and algo optimization to risk management and live market monitoring? What are the leading ways that architectures can accommodate these demands? Our panel of experts will dive into these topics and more.

• Russ Caldwell, Senior Product Manager, Dell EMC

Finance is full of use cases that require integrated analysis of historical and real-time data, ranging from market data and orders to telemetry from machines and applications. For cases that are not super latency-sensitive, firms often turn to data processing frameworks like Spark or Flink and data infrastructure like Kafka and HDFS. According to Russ, the resulting solutions are often brittle and insecure, requiring constant care and feeding to update, secure and manage. In this session, Russ will contend that taking the concept of streaming data deeper into the architecture (streams as a new storage primitive) allows for much greater simplicity while reducing latency and more easily solving common pain points such as exactly-once semantics and atomic transactions. Through real-world use cases, he will argue that using streams as a primitive reduces the infrastructure and engineering costs associated with open source frameworks while shrinking time to market for new data analytic solutions.

• Manoj Narang, CEO, Mana Partners
• Rafman Azeez, MD Technology, BNY Mellon (invited)
• Christin Brown, Global Financial Services Strategy & Solutions Lead, Google Cloud
• Dr. Joe Landman, HPC Architect, HPCaaS in HPC|AI business unit, HPE
• Ehsan Totoni, CTO & Co-founder, Bodo
• Dean Wampler, Head of Developer Relations, Anyscale.com

The pandemic presents financial firms with exceptional uncertainty. The path from uncertainty to action is analysis, but analytic processes built during stable times can have trouble during chaos. Quants responsible for trading, investment, risk, and surveillance strategies are asking new questions of old datasets while applying new data to old questions, all at an unprecedented rate. Workload scales vary dramatically from day to day. For firms to prosper, their analysis must become more agile. Four key technology trends promise to provide that agility: 1) public cloud infrastructure, 2) private cloud frameworks that make on-prem infrastructure elastic, 3) orchestrated containers that present apps with completely abstract infrastructure, and 4) development frameworks that separate apps from infrastructure altogether. How well are these four trends serving financial analytics today? What current and emerging best practices enable quants to easily run analytics--especially Python analytics--at scale? When we give quants such great power to incur costs, how do we ensure they are using resources efficiently? Come join in the debate with two trading and investment firms, two heavyweights of public and private cloud, and two stealth innovators in the Python ecosystem. To kick off, some of the panelists will provide a short presentation:

• Benjamin Maron, FPGA Team Lead, Hudson River Trading
• Dr. Gareth Morris, Chief Hardware Architect, Liquid Capital Markets
• Jon Joshua, Development Lead, BGC Partners
• Dr. Christophe Desmouliers, CTO, Enyx

FPGA is now a mainstream technology in financial markets, from small firms like prop shops to large organizations like agency brokers. But mainstream does not mean mature. Compared to software, the use of FPGA in finance is still young, the number of developers limited, and the ecosystem small. Our expert panel will discuss some of the key challenges, advances, and best practices in FPGA development. For example, what does it mean to test FPGA solutions for finance, and how has the tooling for test and verification advanced in the last few years? What about monitoring, cross-platform support, availability of functionality from third parties, and other practical requirements? How do the answers differ between small organizations obsessed with picoseconds and large enterprises more concerned about processes that scale? Whether your organization is an experienced FPGA shop or is just FPGA-curious, join this session to learn from others’ experiences and ask our panelists what’s on your mind.

• Adam Sherer, Verification Technology Executive, Cadence Design Systems, Inc.

Years ago, a few innovative trading firms started moving critical logic from software to FPGA firmware, a trend that is now widespread. Now a handful of firms are designing their own application-specific integrated circuits (ASICs)—that is, their own customized chips. In this talk, Adam will summarize the unique properties of ASICs and explore different ways to leverage them for low-latency analytics. He will also lay out the ASIC development flow, the investments that are required, and the trade-offs that a firm must weigh, ending with a template for ASIC decision making. Come to ask your questions and get a sense of whether custom ASICs should be in your future.