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Protean Code: Achieving Near-free Online Code Transformations for Warehouse Scale Computers
| Citations: | 6 - 2 self |
BibTeX
@MISC{Laurenzano_proteancode:,
author = {Michael A. Laurenzano and Yunqi Zhang and Lingjia Tang and Jason Mars},
title = {Protean Code: Achieving Near-free Online Code Transformations for Warehouse Scale Computers},
year = {}
}
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Abstract
Abstract—Rampant dynamism due to load fluctuations, co-runner changes, and varying levels of interference poses a threat to application quality of service (QoS) and has limited our ability to allow co-locations in modern warehouse scale computers (WSCs). Instruction set features such as the non-temporal memory access hints found in modern ISAs (both ARM and x86) may be useful in mitigating these effects. However, despite the challenge of this dynamism and the availability of an instruction set mechanism that might help address the problem, a key capability missing in the system software stack in modern WSCs is the ability to dynamically transform (and re-transform) the executing application code to apply these instruction set features when necessary. In this work we introduce protean code, a novel approach for enacting arbitrary compiler transformations at runtime for native programs running on commodity hardware with negligible (<1%) overhead. The fundamental insight behind the underlying mechanism of protean code is that, instead of maintaining full control throughout the program’s execution as with traditional dynamic optimizers, protean code allows the original binary to execute continuously and diverts control flow only at a set of virtualized points, allowing rapid and seamless rerouting to the new code variants. In addition, the protean code compiler embeds IR with high-level semantic information into the program, empowering the dynamic compiler to perform rich analysis and transformations online with little overhead. Using a fully functional protean code compiler and runtime built on LLVM, we design PC3D, Protean Code for Cache Contention in Datacenters. PC3D dynamically employs non-temporal access hints to achieve utilization improvements of up to 2.8x (1.5x on average) higher than state-of-the-art contention mitigation runtime techniques at a QoS target of 98%. Keywords-compiler; dynamic compiler; optimization; cache; resource sharing; datacenter; warehouse scale computer I.
Keyphrases
protean code near-free online code transformation warehouse scale computer dynamic compiler functional protean code compiler resource sharing state-of-the-art contention mitigation runtime technique utilization improvement rich analysis non-temporal memory access hint novel approach seamless rerouting full control new code variant co-runner change key capability application quality instruction set feature original binary qos target little overhead diverts control flow fundamental insight virtualized point system software stack non-temporal access hint native program scale computer cache contention abstract rampant dynamism application code instruction set mechanism modern isas load fluctuation modern wscs arbitrary compiler transformation traditional dynamic optimizers protean code compiler program execution modern warehouse scale computer high-level semantic information commodity hardware
