Archives: 연구 > 연구성과

[Prof. Junil Choi]

 

EE Professor Junil Choi was awarded the Early Achievement Award by the IEEE Communications Society Communication Theory Technical Committee (CTTC), becoming the first Korean member to receive the honor.

Although professor Choi was chosen as the recipient for the 2021 award, the award ceremony was held at the belated Communication Theory Workshop (CTW) last week, due to the COVID-19 pandemic.

The IEEE CTTC was established in 1964 as one of the first technical committees within the IEEE Communications Society (ComSoc).

Since 2016, the CTTC Early Achievement Award has celebrated the achievements of members with early career visibility within 10 years of their Ph.D., with a history of recipients from prestigious institutions such as Stanford University, Imperial College London, Virginia Tech and KTH.

 

[Prof. Minsoo Rhu]

 

 

[Prof. Myoungsoo Jung, Miryeong Kwon, Seungjun Lee, and Hyunkyu Cho from left]

 

Our department’s Professor Myoungsoo Jung’s research team has developed the world’s first Predictable Latency Mode (PLM) SSD based hardware and software co-designed framework for Log-Structured Merge Key-Value Stores (LSM KV store).

 

The research team has developed the ‘hardware and software co-designed framework for LSM KV store, Vigil-KV’ that eliminates long-tail latency by utilizing the Predictable Latency Mode (PLM) interface, which provides constant read latency, to the actual datacenter-scale SSD. Vigil-KV outpoerforms 3.19x faster tail latency and 34% faster average latency compared to the existing LSM KV store.

 

LSM KV store, a kind of database, is used to manage various application data, and it must process the user requests within the requirement time in order not to degrade the user experience. To this end, Vigil-KV enables a predictable latency mode (PLM) interface on an actual datacenter-scale NVMe SSD (PLM SSD), which guarantees constant read latency in deterministic mode related to read service without performing SSD’s internal tasks.

 

Specifically, Vigil-KV hardware makes the deterministic mode SSDs exist in the system to remove SSD’s internal tasks by configuring PLM SSD RAID. In addition, Vigil-KV software prevents the deterministic mode from being released by LSM KV store’s internal tasks, scheduling LSM KV store operations (e.x., compaction/flush operations) and client requests.

 

Among the proposed research results, especially noteworthy is that Vigil-KV is the first work that implements the PLM interface in a real SSD and makes the read latency of LSM KV store deterministic in a hardware-software co-design manner. They prototype Vigil-KV hardware on a 1.92TB datacenter-scale NVMe SSD while implementing Vigil-KV software using Linux 4.19.91 and RocksDB 6.23.0.

 

The KAIST Ph.D. Candidates (Miryeong Kwon, Seungjun Lee, and Hyunkyu Choi) participate in this research, and the paper (Vigil-KV: Hardware-Software Co-Design to Integrate Strong Latency Determinism into Log-Structured Merge Key-Value Stores) was reported in July, 11th at ‘USENIX Annual Technical Conference, ATC, 2022’. In addition, they has won the Best Paper Award from Samsung for this paper (Vigil-KV) with Professor Jae-Hyeok Choi’s research team.

 

The Best Paper Award from Samsung recognizes master’s and doctorate students that participated in research grant projects and published papers related to the project among papers adopted by foreign journals/conferences since September 21st. This year’s awards consisted of grand award (2 people), excellence award (1 person), and encouragement award (2 people).

The research was supported by Samsung. More information on this paper can be found at http://camelab.org.

 

 

 

 

 

 

 

[Prof. Kayoung Lee]

 

KAIST EE Professor Kayoung Lee is selected for the Young Scholar Award at the 9th Korean Symposium on Graphene and 2D Materials, hold by the Korean Graphene Society. 

 

The Young Scholar Award is awarded to those who have made a great contribution to the Korean graphene and 2D materials field, among academics under the age of 40. 

 

Professor Kayoung Lee, as this year’s awardee, received the award with a prize of 1 million wons.

 

[Award ceremony picture, Society Chair, Prof. Jong-Hyun Anh, Prof. Kayoung Lee, from left ]

[Prof. Jae-Woong Jeong, Simok Lee, From Left ]

 

Ph.D. student Simok Lee (Advised by Jae-Woong Jeong) won the Best Paper Award at the 2022 Korean Sensors Society Autumn Conference.

The Korean Sensors Society Conference is a conference held every spring and fall, and this year, and this autumn conference was held in Yeosu from August 24th to 26th.

Ph.D. student Simok Lee has published a paper titled “Adaptive Electronic Skin with High Sensitivity and Large Bandwidth Based on Gallium Microdrop-Elastomer Composite”.

Details are follows. Congratulations once again to Ph.D. student Simok Lee and Professor Jae-Woong Jeong!

 

Conference: 2022 Korean Sensors Society Autumn Conference

 

Date: August 24-26, 2022

 

Award: Best Presentation Paper Award

 

Authors: Simok Lee, Sang-Hyuk Byun, Jae-Woong Jeong (Advisory Professor)

 

Paper Title: Adaptive Electronic Skin with High Sensitivity and Large Bandwidth based on Gallium Microdroplet-Elastomer Composite

 

 

EE Professor Rhu, Minsoo’s Research Team Build First-ever Privacy-aware Artificial Intelligence Semiconductor, Speeding Up the Differentially Private Learning Process 3.6 Times Google’s TPUv3

 

[Professor Rhu, Minsoo]

 

EE Professor Rhu and his research team have taken artificial intelligence semiconductors a big leap forward in the application of differentially private machine learning. Professor Rhu’s team analyzed the bottleneck component in the differentially private machine learning performance and devised a semiconductor chip greatly improving differentially private machine learning application performance.

Professor Rhu’s artificial intelligence chip consists of, among others, a cross-product-based arithmetic unit and an addition tree-based post-processing arithmetic unit and is capable of 3.6 times faster machine learning process compared with that of Google’s TPUv3, today’s most widely used AI processor.

The new chip also boasts comparable performance to that of NVIDIA’s A100 GPU, even with 10 times less resources.

 

[From left, Co-lead authors Park, Beomsik and Hwang, Ranggi; co-authors Yoon, Dongho and Choi, Yoonhyuk]

 

This work, with EE researchers Park, Beomsik and Hwang, Ranggi as co-first authors, will be presented as DiVa: An Accelerator for Differentially Private Machine Learning at the 55th IEEE/ACM International Symposium on Microarchitectures (MICRO 2022), the premier research venue for computer architecture research coming October 1 through 5 in Chicago, USA.

Professor Rhu’s achievements have been reported in multiple press coverage.

 

Links:

AI Times: http://www.aitimes.com/news/articleView.html?idxno=146435

Yonhap : https://www.yna.co.kr/view/AKR20201116072400063?input=1195m

Financial News : https://www.fnnews.com/news/202208212349474072

Donga Science : https://www.dongascience.com/news.php?idx=55893

Industry News : http://www.industrynews.co.kr/news/articleView.html?idxno=46829