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Qi Pei

dblp:291/5262 · DBLP profile ↗
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3ranked-venue papers
3as first author
3since 2021 · last 2024
0009-0009-4241-538XORCID · corroborated

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

Systems, architecture and hardware · 2 · 2 first-author · 2 since 2021Software engineering, systems software and programming languages · 2 · 2 first-author · 2 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
1 paper
Cloud and datacenter computing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing › cloud economics
fair pricing
0.812024
Litmus: Fair Pricing for Serverless Computing · ASPLOS (4) 2024
Cloud and datacenter computing
serverless computing
0.812024
Litmus: Fair Pricing for Serverless Computing · ASPLOS (4) 2024
Cloud and datacenter computing
cluster resource management and scheduling
0.212024
Litmus: Fair Pricing for Serverless Computing · ASPLOS (4) 2024

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

pricing mechanism design · 0.8
YearPublicationVenuePosition
2024 Litmus: Fair Pricing for Serverless Computing
abstract
Serverless computing has emerged as a market-dominant paradigm in modern cloud computing, benefiting both cloud providers and tenants. While service providers can optimize their machine utilization, tenants only need to pay for the resources they use. To maximize resource utilization, these serverless systems co-run numerous short-lived functions, bearing frequent system condition shifts. When the system gets overcrowded, a tenant's function may suffer from disturbing slowdowns. Ironically, tenants also incur higher costs during these slowdowns, as commercial serverless platforms determine costs proportional to their execution times.
Qi Pei, Yipeng Wang 0002, Seunghee Shin
ASPLOS (4)1
2021 Improving the Heavy Re-encryption Overhead of Split Counter Mode Encryption for NVM
abstract
Emerging non-volatile memory technology enables non-volatile main memory (NVMM) that can provide larger capacity and better energy-saving opportunities than DRAMs. However, its non-volatility raises security concerns, where the data in NVMMs can be taken if the memory is stolen. Thereby, the data must stay encrypted outside the processor boundary. Such encryption requires decryption before the data being used by the processor, adding extra latency to the performance-critical read operations. Split counter mode encryption hides the latency but introduces frequent page re-encryptions as a trade-off. We find that such re-encryption overhead worsens on the NVMM, whose slow latency negates prior optimizations.To mitigate the overhead, we re-design the encryption scheme based on two key observations. First, we observe that NVMMs only need counters that can count up to twice their lifetime. Second, we observe diminishing returns on the counter size as increasing the counter size further does not necessarily decrease the re-encryption frequency. Our new designs re-arrange those inefficiently used bits to reduce the re-encryption overhead. In the tests, our two designs, 3-level split counter mode encryption and 8-block split counter mode encryption, effectively reduce the re-encryption overheads by 63% and 66%, which improve performances by 26% and 30% at maximum and by 8% and 9% on average from the original split counter scheme.
Qi Pei, Seunghee Shin
ICCD1
2021 Efficient Split Counter Mode Encryption for NVM
abstract
Emerging non-volatile memory technology enables non-volatile main memory (NVMM) that can provide larger capacity and better energy-saving opportunities than DRAMs. However, its non-volatility raises security concerns, where the data in NVMMs can be taken if the memory is stolen. Memory encryption protects the data by limiting it always stays encrypted outside the processor boundary. However, the decryption latency before the data being used by the processor brings new performance burdens. Unlike DRAM-based main memory, such performance overhead worsens on the NVMM due to the slow latency. In this paper, we will introduce optimizations that can be used to re-design the encryption scheme. In our tests, our two new designs, 3-level split counter mode encryption and 8-block split counter mode encryption, improved performance by 26% and 30% at maximum and by 8% and 9% on average from the original encryption scheme, split counter encryption.
Qi Pei, Seunghee Shin
ISPASS1