EDBT 2026 Demo / reviewers in the wild / expert
Yuvraj Patel
dblp:124/5787
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems
file systems |
1.8 | 5 | 2021 | 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 |
0.9 | 3 | 2021 | 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 |
0.8 | 1 | 2024 | ServerlessLLM: Low-Latency Serverless Inference for Large Language Models · OSDI 2024 |
Cloud and datacenter computing › serverless computing
serverless inference |
0.8 | 1 | 2024 | ServerlessLLM: Low-Latency Serverless Inference for Large Language Models · OSDI 2024 |
Storage systems › non-volatile memory storage
byte-addressable storage |
0.7 | 1 | 2023 | WiscSort: External Sorting For Byte-Addressable Storage · Proc. VLDB Endow. 2023 |
Storage systems › out-of-core computation
external sorting |
0.7 | 1 | 2023 | WiscSort: External Sorting For Byte-Addressable Storage · Proc. VLDB Endow. 2023 |
Storage systems › key-value storage
key-value separation |
0.7 | 1 | 2023 | WiscSort: External Sorting For Byte-Addressable Storage · Proc. VLDB Endow. 2023 |
Storage systems
key-value storage |
0.7 | 1 | 2023 | WiscSort: External Sorting For Byte-Addressable Storage · Proc. VLDB Endow. 2023 |
Memory systems
cache |
0.6 | 1 | 2022 | NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching · FAST 2022 |
Distributed systems
distributed coordination |
0.6 | 1 | 2022 | Using Trātṛ to tame Adversarial Synchronization · USENIX Security Symposium 2022 |
Storage systems › storage management
storage reclamation |
0.6 | 2 | 2017 | 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 |
0.6 | 1 | 2022 | Using Trātṛ to tame Adversarial Synchronization · USENIX Security Symposium 2022 |
Storage systems › storage reliability
durability |
0.5 | 1 | 2021 | Can Applications Recover from fsync Failures? · ACM Trans. Storage 2021 |
Operating systems › resource management › process management
CPU scheduling |
0.4 | 1 | 2020 | Avoiding scheduler subversion using scheduler-cooperative locks · EuroSys 2020 |
Operating systems › resource management › process management › CPU scheduling
proportional share scheduling |
0.4 | 1 | 2020 | Avoiding scheduler subversion using scheduler-cooperative locks · EuroSys 2020 |
Concurrent programming
synchronization |
0.4 | 1 | 2020 | Avoiding scheduler subversion using scheduler-cooperative locks · EuroSys 2020 |
Storage systems › file systems
copy-on-write |
0.4 | 2 | 2017 | 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 |
0.2 | 1 | 2016 | Correlated Crash Vulnerabilities · OSDI 2016 |
Natural language and speech › Language models and text generation
large language model inference |
0.2 | 1 | 2024 | ServerlessLLM: Low-Latency Serverless Inference for Large Language Models · OSDI 2024 |
Operating systems › resource management › storage management
file systems |
0.2 | 2 | 2021 | Can Applications Recover from fsync Failures? · ACM Trans. Storage 2021 Correlated Crash Vulnerabilities · OSDI 2016 |
Memory systems
non-volatile memory |
0.2 | 1 | 2022 | NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching · FAST 2022 |
Operating systems › resource management › process management › CPU scheduling
thread scheduling |
0.1 | 1 | 2020 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 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 |
OSDI | 6 |
| 2023 | WiscSort: External Sorting For Byte-Addressable StorageabstractWe 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 |
FAST | 3 |
| 2022 | Using Trātṛ to tame Adversarial Synchronization
Yuvraj Patel, Chenhao Ye, Akshat Sinha, Abigail Matthews, Andrea C. Arpaci-Dusseau, Michael M. Swift |
USENIX Security Symposium | 1 |
| 2021 | Can Applications Recover from fsync Failures?abstractWe 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. Storage | 2 |
| 2020 | Avoiding scheduler subversion using scheduler-cooperative locksabstractWe 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 |
EuroSys | 1 |
| 2020 | Can Applications Recover from fsync Failures?
Anthony Rebello, Yuvraj Patel, Ramnatthan Alagappan, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau |
USENIX ATC | 2 |
| 2018 | Memory-Oriented Distributed Computing at Rack ScaleabstractNo abstract available. Haris Volos 0001, Kimberly Keeton, Milind Chabbi, Se Kwon Lee, Mark Lillibridge, Yuvraj Patel, Wei Zhang 0052 |
SoCC | 7 |
| 2018 | Revisiting Concurrency in High-Performance NoSQL Databases
Yuvraj Patel, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau |
HotStorage | 1 |
| 2017 | Algorithms and Data Structures for Efficient Free Space Reclamation in WAFL
Ram Kesavan, Travis Grusecki, Yuvraj Patel |
FAST | 4 |
| 2017 | High Performance Metadata Integrity Protection in the WAFL Copy-on-Write File System
Harendra Kumar, Yuvraj Patel, Ram Kesavan, Sumith Makam |
FAST | 2 |
| 2017 | Efficient Free Space Reclamation in WAFLabstractNetApp ® 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. Storage | 4 |
| 2016 | Correlated Crash Vulnerabilities
Ramnatthan Alagappan, Aishwarya Ganesan, Yuvraj Patel, Thanumalayan Sankaranarayana Pillai, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau |
OSDI | 3 |