Collaborative, Tier-Conscious Data Management for Next-Generation Memory Systems

Colloq: Speaker: 
Michael Jantz
Colloq: Speaker Institution: 
University of Tennessee
Colloq: Date and Time: 
Tue, 2017-07-25 10:00
Colloq: Location: 
Building 5700, L202
Colloq: Host: 
Graham Lopez
Colloq: Host Email: 
lopezmg@ornl.gov
Colloq: Abstract: 
A number of promising new memory technologies, such as non-volatile, storage-class memories and high-bandwidth, on-chip RAMs, are beginning to emerge. Since each of these new technologies present tradeoffs distinct from conventional DRAMs, many next-generation systems will include multiple tiers of memory storage, each with their own type of devices. To efficiently utilize the available hardware, such systems will need to alter their data management strategies to consider the performance and capabilities provided by each tier. This talk will present ongoing work to improve compute performance and efficiency by increasing the effectiveness of application data management for heterogeneous memory systems. A key realization behind our approach is that the distribution and usage of memory resources depend upon activities that occur in different layers of the vertical execution stack, including the applications, OS, and hardware. Our work aims to increase coordination among these cross-layer activities in order to address the limitations and inefficiencies of existing solutions. We will describe tools, techniques, and frameworks that we have developed to enable applications to adapt to heterogeneous memory hardware transparently and automatically. We will also show preliminary evaluation, conducted in simulation, that demonstrates that our guidance-based approach outperforms, and can even improve, other state-of-the-art management strategies.
Colloq: Speaker Bio: 
Michael Jantz is an Assistant Professor at the University of Tennessee where he directs the CORSYS laboratory. His research aims to develop compiler and runtime system tools and frameworks to increase application performance and efficiency on modern and next-generation computer hardware.