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Shuichi Ihara

dblp:208/2028 · DBLP profile ↗
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5ranked-venue papers
0as first author
3since 2021 · last 2024
0000-0002-1077-112XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 5 · 3 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
5 papers
Storage systems · 61% Memory systems · 24% Cloud and datacenter computing · 9%

Topics — the 8 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems › file systems
distributed file system
1.322024
Combining Buffered I/O and Direct I/O in Distributed File Systems · FAST 2024
MetaWBC: POSIX-Compliant Metadata Write-Back Caching for Distributed File Systems · SC 2022
Storage systems › file systems › distributed file system
parallel file system
1.332023
Xfast: Extreme File Attribute Stat Acceleration for Lustre · SC 2023
LPCC: hierarchical persistent client caching for lustre · SC 2019
A configurable rule based classful token bucket filter network request scheduler for the lustre file system · SC 2017
Storage systems
file systems
1.222023
Xfast: Extreme File Attribute Stat Acceleration for Lustre · SC 2023
MetaWBC: POSIX-Compliant Metadata Write-Back Caching for Distributed File Systems · SC 2022
Memory systems › cache management › storage caching
metadata caching
0.612022
MetaWBC: POSIX-Compliant Metadata Write-Back Caching for Distributed File Systems · SC 2022
Memory systems › cache management › storage caching
write-back caching
0.612022
MetaWBC: POSIX-Compliant Metadata Write-Back Caching for Distributed File Systems · SC 2022
Memory systems › cache management › storage caching
client-side caching
0.412019
LPCC: hierarchical persistent client caching for lustre · SC 2019
Cloud and datacenter computing
quality of service
0.312017
A configurable rule based classful token bucket filter network request scheduler for the lustre file system · SC 2017
Cloud and datacenter computing
request scheduling
0.312017
A configurable rule based classful token bucket filter network request scheduler for the lustre file system · SC 2017

Methods — techniques the papers use, named apart from their topics

file caching state machine · 0.6POSIX-compliant memory file system · 0.6SSD-based caching · 0.4token bucket filter · 0.3classful qos rules · 0.3
YearPublicationVenuePosition
2024 Combining Buffered I/O and Direct I/O in Distributed File Systems
Yingjin Qian, Marc-Andre Vef, Patrick Farrell, Andreas Dilger, Shuichi Ihara, Yinjin Fu, André Brinkmann
FAST6
2023 Xfast: Extreme File Attribute Stat Acceleration for Lustre
abstract
Directory tree walks on parallel file systems are costly operations frequently required by many storage management tasks. Even listing the contents of a single directory can take minutes to hours for huge directories, as the tree walk performance of parallel file systems in Linux is severely throttled by sequentially accessing distributed metadata for each file through the syscall interface.
Yingjin Qian, Wen Cheng 0003, Lingfang Zeng, Marc-Andre Vef, Andreas Dilger, Siyao Lai, Shuichi Ihara, André Brinkmann
SC8
2022 MetaWBC: POSIX-Compliant Metadata Write-Back Caching for Distributed File Systems
abstract
In parallel and distributed file systems, caching can improve data performance and metadata operations. Currently, most distributed file systems adopt a write-back data cache for performance and a write-through metadata cache for simplifying consistency. However, with modern file systems scales and workloads, write-through metadata caching can impact overall file system performance, e.g., through lock contention and heavy RPC loads required for namespace synchronization and transaction serialization. This paper proposes a novel metadata write-back caching (MetaWBC) mechanism to improve the performance of metadata operations in distributed environments. To achieve extreme metadata performance, we developed a fast, lightweight, and POSIXcompatible memory file system as a metadata cache. Further, we designed a file caching state machine and included other performance optimizations. We coupled MetaWbc with Lustre and evaluated that MetaWbc can outperform the native parallel file system by up to 8x for metadata-intensive benchmarks, and up to 7x for realistic workloads in throughput.
Yingjin Qian, Wen Cheng 0003, Lingfang Zeng, Marc-Andre Vef, Oleg Drokin, Andreas Dilger, Shuichi Ihara, Wusheng Zhang, Yang Wang 0006, André Brinkmann
SC7
2019 LPCC: hierarchical persistent client caching for lustre
abstract
Most high-performance computing (HPC) clusters use a global parallel file system to enable high data throughput. The parallel file system is typically centralized and its storage media are physically separated from the compute cluster. Compute nodes as clients of the parallel file system are often additionally equipped with SSDs. The node internal storage media are rarely well-integrated into the I/O and compute workflows. How to make full and flexible use of these storage media is therefore a valuable research question.
Yingjin Qian, Shuichi Ihara, Andreas Dilger, Carlos Thomaz, Wen Cheng 0003, Lingfang Zeng, Fang Wang 0001, Dan Feng 0001, Tim Süß, André Brinkmann
SC3
2017 A configurable rule based classful token bucket filter network request scheduler for the lustre file system
abstract
HPC file systems today work in a best-effort manner where individual applications can flood the file system with requests, effectively leading to a denial of service for all other tasks. This paper presents a classful Token Bucket Filter (TBF) policy for the Lustre file system. The TBF enforces Remote Procedure Call (RPC) rate limitations based on (potentially complex) Quality of Service (QoS) rules. The QoS rules are enforced in Lustre's Object Storage Servers, where each request is assigned to an automatically created QoS class.
Yingjin Qian, Shuichi Ihara, Lingfang Zeng, Jürgen Kaiser, Tim Süß, André Brinkmann
SC3