Reena Panda

TL;DR: It is illustrated how simple estimates of relative node computational throughput can guide heterogeneity-aware data partitioning algorithms to provide balanced graph cutting decisions to optimize application execution for throughput differences in heterogeneous data centers.

TL;DR: PerfProx enables fast and efficient proxy generation using performance metrics derived primarily from hardware performance counters, and generates miniature proxy benchmarks, which are representative of the performance of real-world applications and yet, converge to results quickly and do not need any complex software-stack support.

TL;DR: This paper proposes a profiling methodology leveraging synthetic graphs for capturing a node's computational capability and guiding graph partitioning in heterogeneous environments with minimal overheads and shows that by sampling the execution of applications on synthetic graphs following a power-law distribution, the computing capabilities of heterogeneous clusters can be captured accurately.

TL;DR: The inherent differences between the characteristics of the different classes of applications are demonstrated and how to arrive at meaningful subsets of benchmarks is demonstrated, which will help in faster and more accurate targeted early hardware system performance evaluation.