D2.2 White-box methodologies, programming abstractions and libraries

TL;DR

This paper presents new white-box methodologies, models, and programming abstractions for energy-efficient data structures on multicore and embedded platforms, with promising preliminary results showing improved performance and energy efficiency.

Contribution

It introduces relaxed cache-oblivious models, a new power model for Myriad1, and optimized concurrent data structures with better energy-performance trade-offs.

Findings

New models consider computation, data movement, architecture, and application properties.

Concurrent trees outperform state-of-the-art in speed and energy efficiency.

Models validated with micro-benchmarks and application benchmarks.

Abstract

This deliverable reports the results of white-box methodologies and early results of the first prototype of libraries and programming abstractions as available by project month 18 by Work Package 2 (WP2). It reports i) the latest results of Task 2.2 on white-box methodologies, programming abstractions and libraries for developing energy-efficient data structures and algorithms and ii) the improved results of Task 2.1 on investigating and modeling the trade-off between energy and performance of concurrent data structures and algorithms. The work has been conducted on two main EXCESS platforms: Intel platforms with recent Intel multicore CPUs and Movidius Myriad1 platform. Regarding white-box methodologies, we have devised new relaxed cache-oblivious models and proposed a new power model for Myriad1 platform and an energy model for lock-free queues on CPU platforms. For Myriad1 platform, the im- proved model now considers both computation and data movement cost as well as architecture and application properties. The model has been evaluated with a set of micro-benchmarks and application benchmarks. For Intel platforms, we have generalized the model for concurrent queues on CPU platforms to offer more flexibility according to the workers calling the data structure (parallel section sizes of enqueuers and dequeuers are decoupled). Regarding programming abstractions and libraries, we have continued investigat- ing the trade-offs between energy consumption and performance of data structures such as concurrent queues and concurrent search trees based on the early results of Task 2.1.The preliminary results show that our concurrent trees are faster and more energy efficient than the state-of-the-art on commodity HPC and embedded platforms.