Time: May 11-12, 2009
Place: Aalborg University, Selma Lagerløfs vej 300, room 0.2.13
In the past decade, four (often correlated) factors have shifted the performance bottleneck of data-intensive commercial workloads from I/O to the processor and memory subsystem. First, storage systems are becoming faster and more intelligent (now disks come complete with their own processors and caches). Second, modern database storage managers aggressively improve locality through clustering, hide I/O latencies using prefetching, and parallelize disk accesses using data striping. Third, main memories have become much larger and often hold the application’s working set. Fourth, the increasing memory/processor speed gap accentuates the importance of processor caches to database performance. Additionally to deep memory hierarchies, however, the new multi-core chips add aggressive parallelism as a first-class requirement for database system scalability and performance.
How is database technology coping with these changes? This course will first motivate the problem of database performance on modern hardware by discussing how database and computer microarchitecture technologies have evolved over the past three decades. We will discuss approaches and methodologies used to produce time breakdowns when executing database workloads on modern processors. Then, we will survey techniques proposed in the literature towards architecture-conscious database systems, and their evaluation. We will emphasize the importance and explain the challenges when determining the optimal data placement on all levels of memory hierarchy, and contrast to other approaches such as prefetching data and instructions. Finally, we will discuss open problems and future directions on that arise on the new multi-core chip platforms.
Anastasia Ailamaki is a professor at EPFL, Lausanne (Switzerland). She is an expert in database system behavior on modern hardware (processor, memory, and disks).