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ARM servers are becoming increasingly common, making server technologies such as virtualization for ARM of growing importance. We present the first study of ARM virtualization performance on server hardware, including multi-core measurements of two popular ARM and x86 hypervisors, KVM and Xen. We show how ARM hardware support for virtualization can enable much faster transitions between VMs and the hypervisor, a key hypervisor operation. However, current hypervisor designs, including both Type 1 hypervisors such as Xen and Type 2 hypervisors such as KVM, are not able to leverage this performance benefit for real application workloads on ARMv8.0. We discuss the reasons why and show that other factors related to hypervisor software design and implementation have a larger role in overall performance. Based on our measurements, we discuss software changes and new hardware features, the Virtualization Host Extensions (VHE), added in ARMv8.1 that bridge the gap and bring ARM's faster VM-to-hypervisor transition mechanism to modern Type 2 hypervisors running real applications.
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A Case for Hardware Memoization in Server CPUs
Server applications exhibit a high degree of code repetition because they handle many similar requests. In turn, repeated execution of the same code, often with identical inputs, highlights an inefficiency in the execution of server software and suggests memoization as a way to improve performance. Memoization has been extensively explored in software, and several hardware- and hardware-assisted memoization schemes have been proposed in the literature. However, these works targeted memoization of mathematical or algorithmic processing, whereas server applications call for a different approach. We observe that the opportunity for memoization in servers arises not from eliminating the repetition of complex computation, but from eliminating the repetition of software orchestration code. This work studies hardware memoization in servers, ultimately focusing on one pattern, instruction sequences starting with indirect jumps.We explore how an out-of-order pipeline can be extended to support memoization of these instruction sequences, demonstrating the potential of hardware memoization for servers. Using 26 applications to make our case (3 CloudSuite workloads and 23 vSwarm serverless functions), we show how targeting just this one pattern of instruction sequences can memoize over 10% (up to 15.6%) of the dynamically executed instructions in these server applications.
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- Award ID(s):
- 1912517
- PAR ID:
- 10558980
- Editor(s):
- Yang, Chia-Lin
- Publisher / Repository:
- IEEE Computer Architecture Letters
- Date Published:
- Journal Name:
- IEEE Computer Architecture Letters
- Volume:
- 23
- Issue:
- 2
- ISSN:
- 1556-6056
- Page Range / eLocation ID:
- 231 to 234
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/LCA.2024.3505075
