Yu Jian Wu

dblp:260/5886 · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2022
—ORCID · none

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Software engineering, systems software and programming languages · 3 · 2 since 2021Systems, architecture and hardware · 1
YearPublicationVenuePosition
2022 XRP: In-Kernel Storage Functions with eBPF
Yuhong Zhong, Yu Jian Wu, Ioannis Zarkadas, Jeffrey Tao, Evan Mesterhazy, Michael Makris, Amy Tai, Ryan Stutsman, Asaf Cidon
OSDI3
2021 BPF for storage: an exokernel-inspired approach
abstract
The overhead of the kernel storage path accounts for half of the access latency for new NVMe storage devices. We explore using BPF to reduce this overhead, by injecting user-defined functions deep in the kernel's I/O processing stack. When issuing a series of dependent I/O requests, this approach can increase IOPS by over 2.5X and cut latency by half, by bypassing kernel layers and avoiding user-kernel boundary crossings. However, we must avoid losing important properties when bypassing the file system and block layer such as the safety guarantees of the file system and translation between physical blocks addresses and file offsets. We sketch potential solutions to these problems, inspired by exokernel file systems from the late 90s, whose time, we believe, has finally come!
Yuhong Zhong, Hongyi Wang 0007, Yu Jian Wu, Asaf Cidon, Ryan Stutsman, Amy Tai
HotOS3
2020 Egalito: Layout-Agnostic Binary Recompilation
abstract
For comprehensive analysis of all executable code, and fast turn-around time for transformations, it is essential to operate directly on binaries to enable profiling, security hardening, and architectural adaptation. Disassembling binaries is difficult, and prior work relies on a process virtual machine to translate references on the fly or inefficient binary code patching. Our Egalito recompiler leverages metadata present in current stripped x86_64 and ARM64 binaries to generate a complete disassembly, and allows arbitrary modifications that may affect program layout without any constraints from the original binary. We utilize our own layout-agnostic intermediate representation, which is low-level enough to make the regeneration of output code predictable, yet supports a dual high-level representation for sophisticated analysis. We demonstrate nine binary tools including a novel continuous code randomization technique where Egalito transforms itself, and software emulation of the control-flow integrity in upcoming hardware. We evaluated Egalito on a large set of Debian packages, completely analyzing 99.9% of a selection of 867 executables and libraries; a majority of 149 applicable Debian packages pass all tests under Egalito. On SPEC CPU 2006, thanks to our binary optimizations, Egalito actually observes a 1.7% performance speedup.
David Williams-King, Hidenori Kobayashi, Kent Williams-King, Graham Patterson, Frank Spano, Yu Jian Wu, Vasileios P. Kemerlis
ASPLOS6