Conferences / STAC Summit
STAC Summit New York, Fall 2019
Oct 17, 2019 · New York Marriott Marquis, New York, NY, United States
- Conference
- STAC Summit Vendor & industry
- Dates
- Oct 17, 2019
- Venue
- New York Marriott Marquis
- Place
- New York, NY, United States
- Format
- In person
- Status
- Past
- Attendance
- —
- Website
- docs.stacresearch.com
- Recorded
- 15 sponsors · 33 speaker appearances
- Notes
- One-day event. Speakers: full agenda as published on the event page; affiliations as listed at the time. No ticket price stated on the event page (STAC Summits are generally free for qualified financial-firm practitioners; not stated for this edition).
Ticket prices
No ticket prices recorded
Sponsors 15
Platinum 1
- Intel · PLATINUM SPONSOR
Gold 8
- Arista · GOLD SPONSORS
- Dell Technologies · GOLD SPONSORS
- Dotscience · GOLD SPONSORS
- Exablaze · GOLD SPONSORS
- Nutanix · GOLD SPONSORS
- Pavilion Data Systems · GOLD SPONSORS
- Tick Tock Networks · GOLD SPONSORS
- VAST Data · GOLD SPONSORS
Speakers and talks 33
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Balaji Prabhakar | Tick Tock Networks | Speaker | Democratizing time sync to level the playing field | — |
| Bjorn Koelbeck | Quobyte | Speaker | Unlimited Linear Scalable Performance - Try That With Your Box | — |
| Boni Bruno | Dell Technologies | Speaker | Simplifying Deep Learning Infrastructure with Dell EMC | — |
| Brett Miller | MemVerge | Speaker | Enabling Low Latency Market Data Applications with Storage Class Memory | — |
| Britt Ewen | Lord Abbett & Co | Speaker | MLOps - A familiar but strange endeavor | — |
| Ciaran Kennedy | Arista | Speaker | Arista financial trading innovations | — |
| Edouard Alligand | QuasarDB | Speaker | Simpler historical updates management | — |
| Edouard Alligand | QuasarDB | Speaker | Drinking from the firehose: streaming ingest benchmarks | — |
| Frederic Leens | Exostiv Labs | Speaker | Do you really know what happens inside your FPGA? | — |
| Gary Kazantsev | Bloomberg | Speaker | MLOps - A familiar but strange endeavor | — |
| Glenn Wright | KX | Speaker | New optimization strategies for in-memory analytics using Optane persistent memory | — |
| J.D. Patel | Intel | Speaker | Why a single C++ API makes sense for heterogeneous compute infrastructure | — |
| Jason White | Exegy | Speaker | Exegy Xero – Setting a New Benchmark for Tick-to-Trade Speed | — |
| Jeff Denworth | VAST Data | Speaker | No More Tiers: Radical Flash Savings to Redefine AI and Market Data Storage Infrastructure | — |
| Jeff Smith | Meta | Speaker | Deep Learning at Scale with PyTorch | — |
| Josh Pantony | Boosted.ai | Speaker | MLOps - A familiar but strange endeavor | — |
| Laurent de Barry | Enyx | Speaker | Cracking the code on FPGA: How Enyx is making hardware performance more accessible. | — |
| Lior Paster | Mellanox | Speaker | Mellanox: Performance, Innovation, Reliability, Openness | — |
| Mark Coleman | Dotscience | Speaker | Chaos and Pain in Machine Learning, and the ‘DevOps for ML Manifesto’ | — |
| Mark Coleman | Dotscience | Speaker | MLOps - A familiar but strange endeavor | — |
| Matt Meinel | Levyx | Speaker | Scale-in Software for Capital Markets Computing | — |
| Matthew Grosvenor | Exablaze | Speaker | How hard could it be? Understanding network traffic at the picosecond level | — |
| Michel Debiche | STAC | Speaker | STAC Update: Big compute | — |
| Michel Debiche | STAC | Speaker | STAC Update: Big data | — |
| Misha Tselman | JPMorgan Chase | Speaker | Enabling ML in an enterprise production platform | — |
| Mutema Pittman | Intel | Speaker | FPGAs accelerating AI for financial services | — |
| Peter Lankford | STAC | Speaker | Drinking from the firehose: streaming ingest benchmarks | — |
| Peter Lankford | STAC | Speaker | STAC Update: Fast Data | — |
| Pierre Gardrat | NovaSparks | Speaker | NBBO and ETF Calculators | — |
| Rajiv Jain | Xilinx | Speaker | Xilinx Alveo, Vitis and Quantitative Finance Library | — |
| Vahan Sardaryan | LDA Technologies | Speaker | Winning the Race: Ultra-Low Latency with LDA | — |
| Victor Yodaiken | FSMTime by FSMLabs | Speaker | In production: better than 100 nanos accuracy with NTP and PTP, fault tolerance, and forensic traceability. | — |
| VR Satish | Pavilion Data Systems | Speaker | NVMe-oF for High Frequency Trading | — |