Thursday, 21. November 2019, 10:00-11:00 in CAB E 72
Speaker: Tamás Hauer, Technical Program Manager, SRE, Google Zurich
Title: Meaningful Availability
Abstract:
High availability is a critical requirement for cloud applications; having a metric that meaningfully captures it is useful for users and system developers. Commonly used benchmarks are either too complex to be actionable or fail to capture the true perception of users, which leads to miscommunication, and suboptimal engineering decisions. We propose two improvements to availability measurements. A novel metric, "user-uptime" directly models user-perceived availability and avoids the bias often found in alternatives. A presentation paradigm "windowed availability" supports a holistic view by integrating timescales from per-minute to monthly granularity and allows to distinguish between many short periods of unavailability or fewer longer ones. We demonstrate the benefits of windowed user-uptime on synthetic models and on production data from Google's G Suite. Today, all G Suite products are instrumented with this novel metric, it is used both to support engineering decisions and to communicate system health to enterprise customers.
Bio:
Tamás Hauer holds a PhD in theoretical physics. After a brief career as a physicist at the Max-Planck-Institut and CERN, he worked as a research associate at the department of Applied Computer Science of the University of West of England, leading a group in the area of semantic web, grid services and health informatics. He was work package leader of the European FP5 Mammogrid and FP6 Health-e-Child projects. As the CTO of the Swiss startup Prodema Medical / McMRI, he led the development of appMRI, a brain MRI image analysis platform to launch and certification as a class IIa medical device. He joined Site Reliability Engineering of Google Zürich in 2016 as a Technical Program Manager, his current interest is data analysis of service level indicators and service level objectives.
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Thursday, 28. November 2019, 10:00-11:00 in CAB E 72
Speaker: Djordje Zegarac and Martin Marciniszyn (Tensor Technologies)
Title: High Frequency Trading and FPGAs
Abstract:
High-Frequency Trading (HFT) platforms were typically implemented in software on traditional CPUs with high performance network adapters. However, the industry-wide race to "Zero Latency" has led the trading world to explore alternative system architectures that would minimize the internal latency. Field-Programmable Gate Arrays (FPGAs) offer the superior performance with deterministic execution while providing custom implementation flexibility. Due to these valuable architectural properties FPGAs became the integral part of HFT industry in accelerating trading solutions and reducing wire to wire latencies. In this talk we are going to outline the general architecture of our system and describe the main design challenges.
Bio:
Djordje Zegarac received the B.Sc. degree in Electrical Engineering from the University of Calgary, Canada in 2011, the M.Sc. degree in Electronics and Microelectronics from Ecole Polytechnique Fédérale de Lausanne and IBM Research, Switzerland in 2014. He worked as an IC Digital Design Engineer at u-blox, and as FPGA SoC Development Engineer at Enclustra, Switzerland. Currently, he is employed by Tensor Technologies as an FPGA Engineer. His main research interest is in the area of ASIC/FPGA design and hardware acceleration.
Martin Marciniszyn received a Ph.D. in Computer Science from ETH Zurich in 2007. Afterwards he spent the largest part of his professional career as a quant researcher at IMC Trading, one of the largest global HFT companies. Currently, he is the CTO of Tensor Technologies.
HG D 22
Details TBA
05.02.2020 10:00 (HG D22)
PhD Defense: Kaan Kara
Title: Specialized Hardware Solutions for In-Database Analytics and Machine Learning
Committee: Gustavo Alonso (ETH), Ce Zhang (ETH), Onur Mutlu (ETH), and Christoph Hagleitner (IBM Research Zurich).
07.02.2020 Room: TBA
PhD Defense: Reto Achermann
Title: On Memory Addressing
Committee: Timothy Roscoe (ETH Zurich) David Basin (ETH Zurich) Gernot Heiser (UNSW and Data61) David Cock (ETH Zurich)