Events

Select event terms to filter by
Sunday January 21, 2018
Start: 21.01.2018 00:00
End: 21.01.2018 00:00
Monday February 19, 2018
Start: 19.02.2018 00:00
Thursday February 22, 2018
Start: 22.02.2018 11:00

 

COMPASS: Computing Platforms Seminar Series

CAB E 72

Speaker : Ioannis Koltsidas (IBM Research Zurich)


Title:
System software for commodity solid-state storage

 

 

 

 

Abstract:

The high-performance storage landscape is being shaped by three main developments: a) Flash memories are scaling to extreme densities (e.g., 3D-TLC, QLC), b) new storage devices offer single-digit microsecond latencies (e.g., SSDs based on 3D-Xpoint memory), c) new standards provide high-performance, efficient access to local (e.g., NVMe) and remote storage (e.g., NVMeoF).

In this talk we present our work on building systems to maximize the benefits of new technologies, targeting commodity hardware environments such as cloud datacenters. Specifically, we focus on: a) Improving performance and endurance of low-cost Flash via a host translation layer, and b) exploiting low-latency NVM devices to reduce the cost and increase the scalability of systems that would otherwise rely on large amounts of DRAM.

Key ingredients in our stack include a storage virtualization layer, an efficient Key-Value storage engine built specifically for the new types of media, and a novel task-based I/O runtime system that enables CPU-efficient, high performance access to storage in a programmer-friendly way. We present an overview of these technologies along with lessons learned while building them, as well as experimental evidence that demonstrate their applicability.

Shortbio:

Ioannis (Yannis) Koltsidas is a Research Staff Member in the Cloud Computing Infrastructure department at the IBM Research Lab in Zurich, Switzerland. In his current role he is leading a team of researchers doing research on next-generation Flash-enabled storage systems, exploitation of Flash memory in host servers, as well as applications of Storage-class Memories, such as Phase-Change Memory. His interests also include distributed scale-out file storage (GPFS, HDFS) and extensions thereof based on open-format magnetic tape. Some of the latest projects he has been involved in include the IBM FlashSystem, the IBM Easy Tier Server for the DS8000 series and the IBM LTFS Enterprise Edition.

Previously, Ioannis received his PhD in Computer Science from the University of Edinburgh, where he was a member of the Database Group at the School of Informatics. His research was supervised by Prof. Stratis Viglas. The focus of his thesis, titled "Flashing Up The Storage Hierarchy", was on database systems and data-intensive systems in general that employ novel storage media, such as NAND Flash SSDs and use novel algorithms and data structures to boost I/O performance. Prior to that, Ioannis completed his undergraduate studies at the Electrical and Computer Engineering Department of the National Techinical University of Athens (NTUA) in Athens, Greece, where he majored in Computer Science. =========

 

Friday February 23, 2018
Start: 23.02.2018 12:15

Lunch Seminar - Spring 2018

Thursday March 01, 2018
Start: 01.03.2018 16:00

 

COMPASS: Computing Platforms Seminar Series

CAB E 72

Speaker: Saughata Ghose, Carnegie Mellon University

Title: How Safe Is Your Storage? A Look at the Reliability and Vulnerability of Modern Solid-State Drives

 

 

 

 

Abstract:

We live in an increasingly data-driven world, where we process and store a much greater amount of data, and we need to reliably keep this data around for a very long time. Today, solid-state drives (SSDs) made of NAND flash memory have become a popular choice for storage, as SSDs offer high storage density and high performance at a low cost. To keep up with consumer demand, manufacturers have been using a number of techniques to increase the density of SSDs. Unfortunately, this density scaling introduces new types of errors that can seriously affect the reliability of the data, and in turn significantly reduce the lifetime of the SSD.

In this talk, I will cover several issues that we have found which affect data reliability and vulnerability on modern SSDs available on the market today. I will explore two such issues in depth, along with solutions we have developed to mitigate or eliminate these issues. First, I will discuss read disturb errors, where reading one piece of data from an SSD can introduce errors into unread pieces of data. Second, I will discuss program interference errors, where writing one piece of data to an SSD can introduce errors both into other pieces of data and to data that has yet to be written. Notably, our findings show that the predominant solution adopted by industry to mitigate program interference actually introduces other interference errors, and exposes security exploits that can be used by malicious applications. For both issues, I will discuss solutions that we have developed based on these error types, which can buy back much of the lost lifetime, and which can eliminate the security exploits.

Shortbio:

Saugata Ghose is a Systems Scientist in the Department of Electrical and Computer Engineering at Carnegie Mellon University. He received dual B.S. degrees in computer science and in computer engineering from Binghamton University, State University of New York, and the M.S. and Ph.D. degrees from Cornell University, where he was the recipient of the NDSEG Fellowship and the ECE Director’s Ph.D. Teaching Assistant Award. He received the Best Paper Award from the DFRWS-EU conference in 2017, for his work on recovering data from solid-state drives. His current research interests include application- and system-aware memory and storage systems, virtual memory management, architectural solutions for large-scale systems, GPUs, and emerging memory technologies. For more information, see his website at https://ece.cmu.edu/~saugatag/.

Friday March 02, 2018
Start: 02.03.2018 10:00

Speaker: Brad Beckmann (AMD Research)

Title: Processor Design for Exascale Computing

Date and Venue: Friday 2nd of March, 2018, at 10:00am, CAB E 72

Abstract:

The US Department of Energy’s exascale computing initiative aims to build supercomputers to solve a wide range of HPC problems, including emerging data science and machine learning problems. The talk will first cover the requirements for exascale computing and highlight various challenges that need to be addressed. The talk will then give an overview of the various technologies that AMD is pursuing to design an Exascale Heterogeneous Processor (EHP), which will serve as the basic building block of an exascale supercomputer. Finally, the talk will conclude by highlighting some of the simulation infrastructure used to evaluate EHP and our effort to open source and share it with the broader research community. Short Bio:

Brad Beckmann has been a member of AMD Research since 2007 and works in Bellevue, WA. Brad completed his PhD degree in the Department of Computer Science at the University of Wisconsin-Madison in 2006 where his doctoral research focused on physical and logical solutions to wire delay in CMP caches. While at AMD Research, he has worked on numerous projects related to memory consistency models, cache coherence, graphics, and on-chip networks. Currently, his primary research focuses on GPU compute solutions and broadening the impact of future AMD Accelerated Processing Unit (APU) servers. Regards, Juan Gómez Luna

Start: 02.03.2018 12:15
Friday March 09, 2018
Start: 09.03.2018 12:15
Wednesday March 14, 2018
Start: 14.03.2018 14:00

 

COMPASS: Computing Platforms Seminar Series

CAB E 72

Speaker: Eric Sedlar, Oracle Labs

 

Title: Why Systems Research Needs Social Science Added to the Computer Science

 

 

 

 

Abstract:

Computer scientists are very good at improving metrics that can be quantified: performance per-core/per-server/per-Watt, scalability, reliability, and are even getting better at a bit fuzzier metrics like accuracy of ML systems. However, it is many of the fuzziest metrics that are driving trends in computing: programmer productivity, usability, cognitive load and/or degree of security provided by a particular system. The biggest trend in computing for the past few decades is the explosion in the use of open-source software in the bulk of computing tasks. This is true even in environments as security-conscious as defense applications, as the stack that needs to execute in an application becomes too complicated for one programmer or one software vendor to comprehend or master. This move to open source software makes most system metrics worse as much of the code run is not optimized for CPU efficiency and may be understood by nobody working for the firm operating the software or its vendors. What is a systems researcher to do in the face of their inconsequential metrics?

Shortbio:

As VP & Technical Director of Oracle Labs, Eric manages a team of close to 200 systems researchers and engineers worldwide. In his tenure in the Labs, Eric has started a number of long-term system research projects that have led to technology transfer into products, including the GraalVM programming language runtime, PGX Parallel Graph Analytics, and the Parfait tool for Program Analysis. His personal research interests have been in the field of data processing and the intersection with compiler technologies. Eric was the co-author of the SIGMOD Best Paper in 2009 and has been an inventor on 85 granted patents.

Friday March 16, 2018
Start: 16.03.2018 12:00
Thursday April 12, 2018
Start: 12.04.2018 11:00

Thursday, 12 April 2018, 11:00-12:00 in CAB E 72

Speaker: Christoph Hagleitner (IBM Research, Rüschlikon)

Title: Heterogeneous Computing Systems for Datacenter and HPC Applications

 

 

 

 

 

Abstract:

For several decades, the technology roadmap has been driven by technology scaling, but it is evident that this will not be sufficient to economically realize large-scale computing applications. Furthermore, the convergence of data-science and HPC leads to significant changes of the workload characteristic of the emerging exascale HPC applications when compared to "classic" HPC applications. Therefore, the innovations that sustain the roadmap towards exascale computing applications come from heterogeneous, dense, workload-optimized systems. In this presentation, I will discuss the current status and show several projects from within IBM Research - Zurich that advance the roadmap towards tomorrows large-scale computing applications.

Short Bio:

Christoph Hagleitner leads the "Heterogeneous Cognitive Computing Systems" group at the IBM Research – Zurich Lab (ZRL) in Ruschlikon, Switzerland. The group focuses on heterogeneous computing systems for cloud datacenters and HPC. Applications include big-data analytics and cognitive computing. He obtained a diploma degree in Electrical Engineering from ETH, Zurich, Switzerland in 1997 and and a Ph.D. degree for a thesis on CMOS-integrated Microsensors from ETH, Zurich, Switzerland in 2002. In 2003 he joined IBM Research to work on the system architecture of a novel probe-storage device (“millipede”-project). In 2008, he started to build up a new research group in the area of accelerator technologies. The team initially focused on on-chip accelerator cores and gradually expanded its research to heterogeneous systems and their applications. 

 

Thursday April 19, 2018
Start: 19.04.2018 11:00

COMPASS: Computing Platforms Seminar Series

CAB E 72

Speaker: Jane Hung (MIT)

Title: The Challenges and Promises of Large-Scale Biological Imaging

 

 

 

 

 

 

Abstract:

Microscopy images contain rich information about the state of cells, tissues, and organisms and are an important part of experiments to address a multitude of basic biological questions and health problems. The Broad Institute of MIT and Harvard’s Imaging Platform works with dozens of collaborators around the world to design and execute large-scale microscopy-based experiments in order to identify the causes and potential cures of disease. These experiments, though carried out in a non-profit environment, have led to the discovery of drugs effective in animal models of disease, and the uncovering of mechanisms underlying other diseases and biological processes.

Most recently, we have been working on software to support the increased physiological complexity of modern screening systems, for example, using whole organisms and co-cultured cell types. As well, our machine learning tools allow a biologists’ intuition to guide the computer to measure subtle phenotypes. We are also working to use patterns of morphological features to group samples by similarity, in order to identify drug targets and gene function. Ultimately, we aim to make microscopy images as computable as other sources of genomic and chemical information.

Short Bio:

Jane received her Ph.D. in the Department of Chemical Engineering at MIT and is interested in how accessible software can make processes more efficient. She had her first computer vision experience at an internship at Novartis in Basel working on automated drug manufacturing monitoring. From there, she joined Anne Carpenter's biological imaging analysis lab at the Broad Institute. She has worked on machine learning-based software application CellProfiler Analyst in collaboration with David Dao as well as deep learning-based object detection software Keras R-CNN in collaboration with Allen Goodman.

---

COMPASS Talks

Thursday April 26, 2018
Start: 26.04.2018 11:00

 

COMPASS: Computing Platforms Seminar Series

CAB E 72

 

Thursday, 26 April 2018, 11:00-12:00 in CAB E 72

Speaker: Spyros Blanas (Ohio State University, USA)

Title: Scaling database systems to high-performance  computers

 

 

 

 

 

Abstract:

Processing massive datasets quickly requires warehouse-scale computers. Furthermore, many massive datasets are multi-dimensional arrays which are stored in formats like HDF5 and NetCDF that cannot be directly queried using SQL. Parallel array database systems like SciDB cannot scale in this environment that offers fast networking but very limited I/O bandwidth to shared, cold storage: merely loading multi-TB array datasets in SciDB would take days--an unacceptably long time for many applications.

In this talk, we will present ArrayBridge, a common interoperability layer for array file formats. ArrayBridge allows scientists to use SciDB, TensorFlow and HDF5-based code in the same file-centric analysis pipeline without converting between file formats. Under the hood, ArrayBridge manages I/O to leverage the massive concurrency of warehouse-scale parallel file systems without modifying the HDF5 API and breaking backwards compatibility with legacy applications. Once the data has been loaded in memory, the bottleneck in many array-centric queries becomes the speed of data repartitioning between different nodes. We will present an RDMA-aware data shuffling abstraction that directly converses with the network adapter in InfiniBand verbs and can repartition data up to 4X faster than MPI. We conclude by highlighting research opportunities that need to be overcome for data processing to scale to warehouse-scale computers.

Short Bio: 

Spyros Blanas is an assistant professor in the Department of Computer Science and Engineering at The Ohio State University. His research interest is high-performance database systems, and his current goal is to build a database system for high-end computing facilities. He has received the IEEE TCDE Rising Star Award and a Google Research Faculty award. He received his Ph.D. at the University of Wisconsin–Madison and part of his Ph.D. dissertation was commercialized in Microsoft's flagship data management product, SQL Server, as the Hekaton in-memory transaction processing engine.

---

COMPASS Talks

Monday April 30, 2018
Start: 30.04.2018 16:15

Date: 30 April 2018

Time: 16:15 - 17:15

Place: ETH Zurich, main campus CAB G 61

Speaker: Prof. Wen-Mei Hwu, University of Illinois at Urbana-Champaign

Host: Prof. Onur Mutlu

ABSTRACT:

We have been experiencing two very important developments in computing. On the one hand, a tremendous amount of resources have been invested into innovative applications such as first-principle based models, deep learning and cognitive computing. On the other hand, the industry has been taking a technological path where traditional scaling is coming to an end and application performance and power efficiency vary by more than two orders of magnitude depending on their parallelism, heterogeneity, and locality. A “perfect storm” is beginning to form from the fact that data movement has become the dominating factor for both power and performance of high-valued applications. It will be critical to match the compute throughput to the data access bandwidth and to locate the compute at where the data is. Much has been and continuously needs to be learned about of algorithms, languages, compilers and hardware architecture in this movement. What are the killer applications that may become the new diver for future technology development? How hard is it to program existing systems to address the date movement issues today? How will we program future systems? How will innovations in memory devices present further opportunities and challenges in designing new systems? What is the impact on long-term software engineering cost on applications (and legacy applications in particular)? In this talk, I will present some lessons learned as we design the IBM-Illinois C3SR Erudite system inside this perfect storm.

 

BIOGRAPHY:

Wen-mei W. Hwu is a Professor and holds the Sanders-AMD Endowed Chair in the Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign. He is also Chief Scientist of UIUC Parallel Computing Institute and director of the IMPACT research group (www.crhc.uiuc.edu/Impact). He co-directs the IBM-Illinois Center for Cognitive Computing Systems Research (C3SR) and serves as one of the principal investigators of the NSF Blue Waters Petascale supercomputer. For his contributions, he received the ACM SigArch Maurice Wilkes Award, the ACM Grace Murray Hopper Award, the IEEE Computer Society Charles Babbage Award, the ISCA Influential Paper Award, the IEEE Computer Society B. R. Rau Award and the Distinguished Alumni Award in Computer Science of the University of California, Berkeley. He is a fellow of IEEE and ACM. Dr. Hwu received his Ph.D. degree in Computer Science from the University of California, Berkeley.

---

 D-INFK Distinguished Colloquium

Wednesday May 09, 2018
Start: 09.05.2018 14:00

 

COMPASS: Computing Platforms Seminar Series

CAB E 72

Speaker: Bastian Hossbach (Oracle Labs)

 

Title: Modern programming languages and code generation in the Oracle Database

 

 

 

 

Abstract:

In this talk, we will present the Oracle Database Multilingual Engine (MLE). MLE is an experimental feature for the Oracle Database that enables developers to write stored procedures and user-defined functions in modern programming languages such as JavaScript and Python. Special attention was payed to embrace the rich ecosystems of tools and libraries developed for those languages in order to make the developer's experience as familiar as possible. We will show several demos of MLE in action and discuss the challenges of integrating a language runtime with a database system. Under the hood, MLE is powered by the speculative JIT compiler Graal. Having a modern JIT compiler inside a database system not only allows for efficiently running user-defined code, but also for runtime compilation and specialization of SQL expressions and other parts of a query plan to speed up overall query execution.

Short Bio:

Since 2015, Bastian is a researcher at Oracle Labs in Zurich, Switzerland. He is currently working on a high-performance query execution engine for database management systems that is capable of executing query plans combined with user-defined scripts written in a variety of languages (e.g., JavaScript, Python). Bastian received a PhD degree in computer science from the University of Marburg, Germany, in 2015. Prior to Oracle Labs, he has been involved in several projects in the areas of data analytics, data processing and IT security.

Wednesday May 16, 2018
Start: 16.05.2018 11:00

Wednesday, 16 May 2018, 11:00-12:00 in CAB E 72

Speaker: Carsten Binnig (TU Darmstadt)

Title: Towards Interactive Data Exploration

 

 

 

Abstract:

Technology has been the key enabler of the current Big Data movement. Without open-source tools like R and Hadoop, as well as the advent of cheap, abundant computing and storage in the cloud, the ongoing trend toward datafication of almost every research field and industry could never have occurred. However, the current Big Data tool set is ill-suited for interactive data exploration of new data making the knowledge discovery process a major bottleneck in our data-driven society.

In this talk, I will first give an overview of challenges for interactive data exploration on large data sets and then present current research results that revisit the design of existing data management systems, from the query interface over the execution models to the storage and the underlying hardware to enable interactive data exploration.

Short Bio:

Carsten Binnig is a Full Professor in the Computer Science department at at TU Darmstadt and an Adjunct Associate Professor in the Computer Science department at Brown University. Carsten received his PhD at the University of Heidelberg in 2008. Afterwards, he spent time as a postdoctoral researcher in the Systems Group at ETH Zurich and at SAP working on in-memory databases. Currently, his research focus is on the design of data management systems for modern hardware as well as modern workloads such as interactive data exploration and machine learning. He has recently been awarded a Google Faculty Award and a VLDB Best Demo Award for his research.