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Monday September 16, 2019
Thursday September 19, 2019
Start: 19.09.2019 10:00

Thursday, 19. September 2019, 10:00-11:00 in CAB E 72

 Speakers: Martin Hentschel/Max Heimel (Snowflake) 

Title: File Metadata Management at Snowflake

 

 

 

Abstract:

Snowflake is an analytic data warehouse offered as a fully-managed service in the cloud. It is faster, easier to use, and far more scalable than traditional on-premise data warehouse offerings and is used by thousands of customers around the world. Snowflake's data warehouse is not built on an existing database or "big data" software platform such as Hadoop—it uses a new SQL database engine with a unique architecture designed for the cloud. This talk provides an overview of Snowflake’s architecture that was designed to efficiently support complex analytical workloads in the cloud. Looking at the lifecycle of micro partitions, this talk explains pruning, zero-copy cloning, and instant time travel. Pruning is a technique to speed up query processing by filtering out unnecessary micro partitions during query compilation. Zero-copy cloning allows to create logical copies of the data without duplicating physical storage. Instant time travel enables the user to query data "as of" a time in the past, even if the current state of the data has changed. This talk also shows how micro partitions tie into Snowflake's unique architecture of separation of storage and compute, and enable advanced features such as automatic clustering.

Speakers bio:

Martin Hentschel received a PhD in Computer Science from the Systems Group at ETH Zurich in 2012. In the following he worked at Microsoft where he built products integrating data from social networks into the Bing search engine. In 2014, he joined Snowflake where he is working on security, meta data management, and stateful micro services.

Max Heimel holds a PhD in Computer Science from the Database and Information Management Group at TU Berlin. He joined Snowflake in 2015 and is working primarily in the areas of query execution and query optimization. Before joining Snowflake, Max worked at IBM and spent several internships at Google.  


COMPASS TALKS

Thursday September 26, 2019
Start: 26.09.2019 10:00

Thursday, 26. September 2019, 10:00-11:00 in CAB E 72

Speaker: Ben Zhao (University of Chicago).

Title: Hidden Backdoors in Deep Learning Systems

 

 

 

 

Abstract:

Lack of transparency in today’s deep learning systems has paved the way for a new type of threats, commonly referred to as backdoor or Trojan attacks. In a backdoor attack, a malicious party can corrupt a deep learning model (either at initial training time or later) to embed hidden classification rules that do not interfere with normal classification, unless an unusual “trigger” is applied to the input, which would then produce unusual (and likely incorrect) results. For example, a facial recognition model with a backdoor might recognize anyone with a pink earring as Elon Musk. Backdoor attacks have been validated in a number of image classification applications, and are difficult to detect given the black-box nature of most DNN models.

In this talk, I will describe two recent results on detecting and understanding backdoor attacks on deep learning systems. I will first present Neural Cleanse (S&P 2019), the first robust tool to detect a wide range of backdoors in deep learning models. We use the idea of inter-label perturbation distances to detect when a backdoor trigger has created shortcuts to misclassification to a particular label. Second, I will describe our new work on Latent Backdoors (CCS 2019), a stronger type of backdoor attacks that are more difficult to detect, and survives retraining in commonly used transfer learning systems. We use experimental validation to show that latent backdoors can be quite robust and stealthy, even against the latest detection tools (including neural cleanse). There are no known techniques to detect latent backdoors, but we present alternative techniques to defend against them via disruption.

Bio:

Ben Zhao is the Neubauer Professor of Computer Science at University of Chicago. He completed his PhD from Berkeley (2004) and his BS from Yale (1997). He is an ACM distinguished scientist, and recipient of the NSF CAREER award, MIT Technology Review's TR-35 Award (Young Innovators Under 35), ComputerWorld Magazine's Top 40 Tech Innovators award, Google Faculty award, and IEEE ITC Early Career Award. His work has been covered by media outlets such as Scientific American, New York Times, Boston Globe, LA Times, MIT Tech Review, and Slashdot. He has published more than 160 publications in areas of security and privacy, networked systems, wireless networks, data-mining and HCI (H-index > 60). He recently served as PC chair for World Wide Web Conference (WWW 2016) and the Internet Measurement Conference (IMC 2018), and is a general cochair for Hotnets 2020. 


 

Thursday October 10, 2019
Start: 10.10.2019 10:00

Thursday, 10. October 2019, 10:00-11:00 in CAB E 72

Speaker: Norman May (SAP Research)

Title: Exploiting modern hardware in SAP HANA

Abstract:

SAP HANA has a long history of exploiting modern hardware to achieve high performance for database workloads. As a recent trend GPUs and FGPAs have the potential to offload work from general purpose CPUs or even accelerate operations previously executed on CPUs. In this talk I will share ongoing work in SAP HANA and potential application scenarios for accelerators along the query processing pipeline. I will also discuss current limitations for the usage of accelerators in productive SAP HANA scenarios.

Short Bio:

Norman May is a database architect and researcher of the HANA core database engine working on query processing and effective resource management. He supervises the research of several students in the SAP HANA campus and actively contributes to the database research community.


COMPASS TALKS

 

Sunday January 19, 2020
Monday January 20, 2020
Tuesday January 21, 2020
Wednesday January 22, 2020
Start: 19.01.2020
End: 22.01.2020