Yuvraj Patel

dblp:124/5787 · DBLP profile ↗
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13ranked-venue papers
3as first author
5since 2021 · last 2024
—ORCID · none

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

Systems, architecture and hardware · 9 · 2 first-author · 2 since 2021Databases, data management, data science and information retrieval · 4 · 2 since 2021Software engineering, systems software and programming languages · 2 · 1 since 2021Security and privacy · 1 · 1 first-author · 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
10 papers
Storage systems · 71% Cloud and datacenter computing · 14% Memory systems · 7%
Software engineering, system software, and programming languages
3 papers
Operating systems · 74% Concurrent programming · 26%
Theoretical computer science
2 papers
Distributed computing theory · 87% Algorithms and data structures · 13%

Topics — the 22 heaviest of 26, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems
file systems
1.852021
Can Applications Recover from fsync Failures? · ACM Trans. Storage 2021
Can Applications Recover from fsync Failures? · USENIX ATC 2020
Efficient Free Space Reclamation in WAFL · ACM Trans. Storage 2017
Storage systems
storage reliability
0.932021
Can Applications Recover from fsync Failures? · ACM Trans. Storage 2021
Correlated Crash Vulnerabilities · OSDI 2016
Can Applications Recover from fsync Failures? · USENIX ATC 2020
Cloud and datacenter computing
serverless computing
0.812024
ServerlessLLM: Low-Latency Serverless Inference for Large Language Models · OSDI 2024
Cloud and datacenter computing › serverless computing
serverless inference
0.812024
ServerlessLLM: Low-Latency Serverless Inference for Large Language Models · OSDI 2024
Storage systems › non-volatile memory storage
byte-addressable storage
0.712023
WiscSort: External Sorting For Byte-Addressable Storage · Proc. VLDB Endow. 2023
Storage systems › out-of-core computation
external sorting
0.712023
WiscSort: External Sorting For Byte-Addressable Storage · Proc. VLDB Endow. 2023
Storage systems › key-value storage
key-value separation
0.712023
WiscSort: External Sorting For Byte-Addressable Storage · Proc. VLDB Endow. 2023
Storage systems
key-value storage
0.712023
WiscSort: External Sorting For Byte-Addressable Storage · Proc. VLDB Endow. 2023
Memory systems
cache
0.612022
NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching · FAST 2022
Distributed systems
distributed coordination
0.612022
Using Trātṛ to tame Adversarial Synchronization · USENIX Security Symposium 2022
Storage systems › storage management
storage reclamation
0.622017
Efficient Free Space Reclamation in WAFL · ACM Trans. Storage 2017
Algorithms and Data Structures for Efficient Free Space Reclamation in WAFL · FAST 2017
Distributed computing theory › fault tolerance
byzantine fault tolerance
0.612022
Using Trātṛ to tame Adversarial Synchronization · USENIX Security Symposium 2022
Storage systems › storage reliability
durability
0.512021
Can Applications Recover from fsync Failures? · ACM Trans. Storage 2021
Operating systems › resource management › process management
CPU scheduling
0.412020
Avoiding scheduler subversion using scheduler-cooperative locks · EuroSys 2020
Operating systems › resource management › process management › CPU scheduling
proportional share scheduling
0.412020
Avoiding scheduler subversion using scheduler-cooperative locks · EuroSys 2020
Concurrent programming
synchronization
0.412020
Avoiding scheduler subversion using scheduler-cooperative locks · EuroSys 2020
Storage systems › file systems
copy-on-write
0.422017
Efficient Free Space Reclamation in WAFL · ACM Trans. Storage 2017
High Performance Metadata Integrity Protection in the WAFL Copy-on-Write File System · FAST 2017
Storage systems
crash consistency
0.212016
Correlated Crash Vulnerabilities · OSDI 2016
Natural language and speech › Language models and text generation
large language model inference
0.212024
ServerlessLLM: Low-Latency Serverless Inference for Large Language Models · OSDI 2024
Operating systems › resource management › storage management
file systems
0.222021
Can Applications Recover from fsync Failures? · ACM Trans. Storage 2021
Correlated Crash Vulnerabilities · OSDI 2016
Memory systems
non-volatile memory
0.212022
NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching · FAST 2022
Operating systems › resource management › process management › CPU scheduling
thread scheduling
0.112020
Avoiding scheduler subversion using scheduler-cooperative locks · EuroSys 2020

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

trātṛ · 1.1failure injection · 1.0empirical characterization · 1.0thread pool sizing · 0.7interference-aware scheduling · 0.7free space reclamation · 0.6space reclamation algorithms · 0.3data structure design · 0.3
YearPublicationVenuePosition
2024 ServerlessLLM: Low-Latency Serverless Inference for Large Language Models
Yao Fu 0013, Leyang Xue, Yeqi Huang, Andrei-Octavian Brabete, Dmitrii Ustiugov, Yuvraj Patel, Luo Mai
OSDI6
2023 WiscSort: External Sorting For Byte-Addressable Storage
abstract
We present WiscSort, a new approach to high-performance concurrent sorting for existing and future byte-addressable storage (BAS) devices. WiscSort carefully reduces writes, exploits random reads by splitting keys and values during sorting, and performs interference-aware scheduling with thread pool sizing to avoid I/O bandwidth degradation. We introduce the BRAID model which encompasses the unique characteristics of BAS devices. Many state-of-the-art sorting systems do not comply with the BRAID model and deliver sub-optimal performance, whereas WiscSort demonstrates the effectiveness of complying with BRAID. We show that WiscSort is 2-7 x faster than competing approaches on a standard sort benchmark. We evaluate the effectiveness of key-value separation on different key-value sizes and compare our concurrency optimizations with various other concurrency models. Finally, we emulate generic BAS devices and show how our techniques perform well with various combinations of hardware properties.
Vinay Banakar, Yuvraj Patel, Kimberly Keeton, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
Proc. VLDB Endow.3
2022 NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching
Kaiwei Tu, Yuvraj Patel, Rathijit Sen, Kwanghyun Park 0001, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
FAST3
2022 Using Trātṛ to tame Adversarial Synchronization
Yuvraj Patel, Chenhao Ye, Akshat Sinha, Abigail Matthews, Andrea C. Arpaci-Dusseau, Michael M. Swift
USENIX Security Symposium1
2021 Can Applications Recover from fsync Failures?
abstract
We analyze how file systems and modern data-intensive applications react to fsync failures. First, we characterize how three Linux file systems (ext4, XFS, Btrfs) behave in the presence of failures. We find commonalities across file systems (pages are always marked clean, certain block writes always lead to unavailability) as well as differences (page content and failure reporting is varied). Next, we study how five widely used applications (PostgreSQL, LMDB, LevelDB, SQLite, Redis) handle fsync failures. Our findings show that although applications use many failure-handling strategies, none are sufficient: fsync failures can cause catastrophic outcomes such as data loss and corruption. Our findings have strong implications for the design of file systems and applications that intend to provide strong durability guarantees.
Anthony Rebello, Yuvraj Patel, Ramnatthan Alagappan, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
ACM Trans. Storage2
2020 Avoiding scheduler subversion using scheduler-cooperative locks
abstract
We introduce the scheduler subversion problem, where lock usage patterns determine which thread runs, thereby subverting CPU scheduling goals. To mitigate this problem, we introduce Scheduler-Cooperative Locks (SCLs), a new family of locking primitives that controls lock usage and thus aligns with system-wide scheduling goals; our initial work focuses on proportional share schedulers. Unlike existing locks, SCLs provide an equal (or proportional) time window called lock opportunity within which each thread can acquire the lock. We design and implement three different scheduler-cooperative locks that work well with proportional-share schedulers: a user-level mutex lock (u-SCL), a reader-writer lock (RW-SCL), and a simplified kernel implementation (k-SCL). We demonstrate the effectiveness of SCLs in two user-space applications (UpScaleDB and KyotoCabinet) and the Linux kernel. In all three cases, regardless of lock usage patterns, SCLs ensure that each thread receives proportional lock allocations that match those of the CPU scheduler. Using microbenchmarks, we show that SCLs are efficient and achieve high performance with minimal overhead under extreme workloads.
Yuvraj Patel, Leon Yang, Leo Prasath Arulraj, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau, Michael M. Swift
EuroSys1
2020 Can Applications Recover from fsync Failures?
Anthony Rebello, Yuvraj Patel, Ramnatthan Alagappan, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
USENIX ATC2
2018 Memory-Oriented Distributed Computing at Rack Scale
abstract
No abstract available.
Haris Volos 0001, Kimberly Keeton, Milind Chabbi, Se Kwon Lee, Mark Lillibridge, Yuvraj Patel, Wei Zhang 0052
SoCC7
2018 Revisiting Concurrency in High-Performance NoSQL Databases
Yuvraj Patel, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
HotStorage1
2017 Algorithms and Data Structures for Efficient Free Space Reclamation in WAFL
Ram Kesavan, Travis Grusecki, Yuvraj Patel
FAST4
2017 High Performance Metadata Integrity Protection in the WAFL Copy-on-Write File System
Harendra Kumar, Yuvraj Patel, Ram Kesavan, Sumith Makam
FAST2
2017 Efficient Free Space Reclamation in WAFL
abstract
NetApp ® WAFL ® is a transactional file system that uses the copy-on-write mechanism to support fast write performance and efficient snapshot creation. However, copy-on-write increases the demand on the file system to find free blocks quickly, which makes rapid free space reclamation essential. Inability to find free blocks quickly may impede allocations for incoming writes. Efficiency is also important, because the task of reclaiming free space may consume CPU and other resources at the expense of client operations. In this article, we describe the evolution (over more than a decade) of the WAFL algorithms and data structures for reclaiming space with minimal impact to the overall performance of the storage appliance.
Ram Kesavan, Travis Grusecki, Yuvraj Patel
ACM Trans. Storage4
2016 Correlated Crash Vulnerabilities
Ramnatthan Alagappan, Aishwarya Ganesan, Yuvraj Patel, Thanumalayan Sankaranarayana Pillai, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
OSDI3