Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
Another list highlighting Open Source Software Releases.
Second GraphLab workshop should be even bigger than the first! GraphLab is a new programming framework for graph-style data analytics.
Reducing the Cost of Persistence for Nonvolatile Heaps in End User Devices
Proceedings of the 20th International Symposium on High-Performance Computer Architecture (HPCA'14), February 2014.
Sudarsun Kannan, Ada Gavrilovska, Karsten Schwan
Georgia Institute of Technology
This paper explores the performance implications of using future byte addressable non-volatile memory (NVM) like PCM in end client devices. We explore how to obtain dual benefits -- increased capacity and faster persistence -- with low overhead and cost. Specifically, while increasing memory capacity can be gained by treating NVM as virtual memory, its use of persistent data storage incurs high consistency (frequent cache flushes) and durability (logging for failure) overheads, referred to as 'persistence cost'. These not only affect the applications causing them, but also other applications relying on the same cache and/or memory hierarchy. This paper analyzes and quantifies in detail the performance overheads of persistence, which include (1) the aforementioned cache interference as well as (2) memory allocator overheads, and finally, (3) durability costs due to logging. Novel solutions to overcome such overheads include (1) a page contiguity algorithm that reduces interference-related cache misses, (2) a cache efficient NVM write aware memory allocator that reduces cache line flushes of allocator state by 8X, and (3) hybrid logging that reduces durability overheads substantially. With these solutions, experimental evaluations with different end user applications and SPEC2006 benchmarks show up to 12% reductions in cache misses, thereby reducing the total number of NVM writes.
FULL PAPER: pdf