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Data Processing on Modern Hardware

Course Description

The roots of many productive database systems today date back thirty years or more. Prominent systems such as IBM's System R or the then-research prototype Ingres were first developed in the 1970s and were designed to address the hardware landscape of the time: disks or even tapes were the only medium to hold reasonable amounts of data; main memory could be considered as truly random access; and the major cost factor in database processing was I/O.

Since that time, computer architectures have changed significantly. RAM chips have become cheap enough to make in-memory processing feasible; caches and other architectural details lead to non-uniform memory access cost (an increasingly relevant performance factor); and the omnipresence of multi-core systems adds a whole new class of complexity to the problem.

In this course we look at how architectural changes affect database systems. Rather than suffering from the increasing latency gap for accesses to main memory, for instance, we can use available CPU caches to our advantage. A cache-aware design can improve the performance of a database operation by orders of magnitude. Likewise, modern CPU features (such as vector instructions) or specialized CPUs (like IBM's Cell processor or the nVidia CUDA architecture) can accelerate database tasks if the respective implementation has beed designed carefully.

We will complement this course with many hands-on exercises, where we verify some of the presented techniques on commodity hardware.

Lecture Slides

Description PDF last updated
Introduction PDF Sep 25, 2011
Cache Awareness PDF Oct 3, 2011
Instruction Execution PDF Oct 17, 2011
Vectorization PDF Oct 31, 2011
Multiple Cores PDF Nov 13, 2011
GPUs PDF Nov 28, 2011
FPGAs PDF Dec 12, 2011

Exercises

Description   PDF   last updated   Resources   Solutions
Assignment1:  Probing your Cache   PDF   Oct 10, 2011   none   src-solution-01.tar.bz2
Assignment2:  Cache Awareness in Databases   PDF   Oct 24, 2011   src-handout-02.tar.bz2   src-solution-02.tar.bz2
Assignment3:  Partitioned Hash Join   PDF   Nov 07, 2011   src-handout-03.tar.bz2   src-solution-03.tar.bz2
Assignment4:  Vectorized (de)compression   PDF   Oct 29, 2011   src-handout-04.tar.bz2   src-solution-04.tar.bz2
Assignment5:  Parallel Partitioned Hash Join   PDF   Dec 05, 2011   src-handout-05.tar.bz2   src-solution-05.tar.bz2
Assignment6:  Query Execution on GPGPUs   PDF   Dec 13, 2011   src-handout-06.tar.bz2   src-solution-06.tar.bz2

Slides Exercise Class

Description   PDF   PDF 2x4   last updated
Exercise Session 1   PDF   PDF 2x4   Sep 26, 2011
Exercise Session 2   PDF   PDF 2x4   Oct 03, 2011
Exercise Session 3   PDF   PDF 2x4   Oct 10, 2011
Exercise Session 4   PDF   PDF 2x4   Oct 17, 2011
Exercise Session 5   PDF   PDF 2x4   Oct 24, 2011
Exercise Session 6   PDF   PDF 2x4   Oct 31, 2011
Exercise Session 7   PDF   PDF 2x4   Nov 07, 2011
Exercise Session 8   PDF   PDF 2x4   Nov 18, 2011
Exercise Session 9   PDF   PDF 2x4   Nov 21, 2011
Exercise Session 10   PDF   PDF 2x4   Nov 28, 2011
Exercise Session 11a   PDF   PDF 2x4   Dec 05, 2011
Exercise Session 11b   PDF   PDF 2x4   Dec 05, 2011
Exercise Session 12   PDF   PDF 2x4   Dec 12, 2011

Material

This course is mostly based on very recent research work that is not (yet) covered in textbooks. Throughout the course we will give references to research papers (mostly published at major database conferences like VLDB or SIGMOD) for background reading.

Another important source are going to be the lecture slides for this course, which we will post on this website as the semester progresses.

Course Hours

Lecture
Mon, 9−11h, room CAB G 59 ― Instructor: Jens Teubner
Exercises
Mon, 11−12h, room CAB G 59 ― Instructor: Louis Woods

Additional Information

This course will be taught in english and is listed as course number 263-3502-00 in the ETH course catalog. You'll get 4 credit points for this 2V + 1Ü course.

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