Computing Platforms Seminar Series (COMPASS)

The Computing Platforms Seminar Series (COMPASS) is focused on talks by industry and academia around the general topic of computing platforms.

COMPASS is held on most Thursdays during the semester 11:00-12:00 (with some exceptions) in CAB E 72.

Upcoming Talks:

Thursday, 24 May 2018, 11:00-12:00 in CAB E 72

Speaker: Cagri Balkesen (Oracle Labs)

Title: RAPID: In-Memory Analytical Query Processing Engine with Extreme Performance per Watt

 

 

 

Abstract:

Today, an ever increasing amount of transistors are packed into processor designs with extra features to support a broad range of  applications. As a consequence, processors are becoming more and more complex and power hungry. At the same time, they only sustain an  average performance for a wide variety of applications while not providing the best performance for specific applications. In this paper, we demonstrate through a carefully designed modern data processing system called RAPID and a simple, low-power processor  specially tailored for data processing that at least an order of  magnitude performance/power improvement in SQL processing can be achieved over a modern system running on today's complex processors.  RAPID is designed from the ground up with hardware/ software co-design  in mind to provide architecture-conscious extreme performance while  consuming less power in comparison to the modern database systems. The  paper presents in detail the design and implementation of RAPID, a relational, columnar, in-memory query processing engine supporting analytical query workloads.

Short bio: 

Cagri completed his PhD in 2014 in the Systems Group at ETH Zurich supervised by Prof. Gustavo Alonso. His broader research interests are data processing on modern computing architectures as well as data stream processing. He holds a MSc in Computer Science of ETH Zurich and a BSc in Computer Engineering of the Middle East Technical University (METU) in Turkey. His PhD thesis at ETH Zurich addresses the design and implementation of in-memory joins on modern hardware architectures with massive multi-core parallelism and the paradigm shift towards in-memory processing. His work on main-memory hash joins received the Best-Paper Runner-Up award at IEEE ICDE 2013. Cagri was a recipient of Excellence Scholarship from ETH Zurich and he holds several US-patents based on his work at IBM and Oracle Labs.


Friday, 6 July 2018, 11:00-12:00 in CAB E 72

Speaker: Martin Burtscher (Texas State University) 

Title: Automatic Hierarchical Parallelization of Linear Recurrences

 

 

 

Abstract:

Many important computations from various fields are instances of linear recurrences. Prominent examples include prefix sums in parallel processing and recursive filters in digital signal processing. Later result values depend on earlier result values in recurrences, making it a challenge to compute them in parallel. We present a brand-new work-, space-, and communication-efficient algorithm to compute linear recurrences that is based on Fibonacci numbers, amenable to automatic parallelization, and suitable for GPUs. We implemented our approach in a small compiler that translates recurrences expressed in signature notation into CUDA code. Moreover, we discuss the domain-specific optimizations performed by our compiler to produce state-of-the-art implementations of linear recurrences. Compared to the fastest prior GPU codes, all of which only support certain types of recurrences, our automatically parallelized code performs on par or better in most cases. In fact, for standard prefix sums and single-stage IIR filters, it reaches the throughput of memory copy for large inputs, which cannot be surpassed. On higher-order prefix sums, it performs nearly as well as the fastest handwritten code. On tuple-based prefix sums and 1D recursive filters, it outperforms the fastest preexisting implementations.

Shirt Bio:

Martin Burtscher is a Professor in the Department of Computer Science at Texas State University. He received the BS/MS degree from ETH Zurich and the PhD degree from the University of Colorado at Boulder. Martin's current research focuses on parallelization of complex programs for GPUs as well as on automatic synthesis of data-compression algorithms. He has co-authored over 100 peer-reviewed scientific publications. Martin is a distinguished member of the ACM and a senior member of the IEEE.


 

Past COMPASS Talks:  

Date Speaker Affiliation Talk
16.05.2018 Carsten Binnig TU Darmstadt Towards Interactive Data Exploration
09.05.2018 Bastian Hossbach Oracle Labs Modern programming languages and code generation in the Oracle Database
26.04.2018 Spyros Blanas Ohio State University Scaling database systems to high-performance computers
19.04.2018 Jane Hung MIT The Challenges and Promises of Large-Scale Biological Imaging
12.04.2018 Christoph Hagleitner IBM Research Heterogeneous Computing Systems for Datacenter and HPC Applications
14.03.2018  Eric Sedlar
 Oracle Labs
Why Systems Research Needs Social Science Added to the Computer Science
01.03.2018 Saughata Ghose Carnegie Mellon University How Safe Is Your Storage? A Look at the Reliability and Vulnerability of Modern Solid-State Drives
22.02.2018  Ioannis Koltsidas IBM Research Zurich System software for commodity solid-state storage