Research Output per year
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
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Program processors
Engineering & Materials Science
Data storage equipment
Engineering & Materials Science
Computer programming languages
Engineering & Materials Science
Decoding
Engineering & Materials Science
Algebra
Engineering & Materials Science
Finite automata
Engineering & Materials Science
Synchronization
Engineering & Materials Science
Memory architecture
Engineering & Materials Science
Network
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Research Output 1996 2019
Self-learnable cluster-based prefetching method for DRAM-flash hybrid main memory architecture
Yoon, S. K., Youn, Y. S., Burgstaller, B. & Kim, S. D., 2019 Jan 1, In : ACM Journal on Emerging Technologies in Computing Systems. 15, 1, 10.Research output: Contribution to journal › Article
Memory architecture
Flash memory
Data storage equipment
Energy utilization
Scalability
Regression prefetcher with preprocessing for DRAM-PCM hybrid main memory
Yun, J. T., Yoon, S. K., Kim, J. G., Burgstaller, B. & Kim, S-D., 2018 Jul 1, In : IEEE Computer Architecture Letters. 17, 2, p. 163-166 4 p.Research output: Contribution to journal › Article
Pulse code modulation
Dynamic random access storage
Data storage equipment
Processing
Energy utilization
Safe non-blocking synchronization in Ada2x
Blieberger, J. & Burgstaller, B., 2018 Jan 1, Reliable Software Technologies – Ada-Europe 2018 - 23rd Ada-Europe International Conference on Reliable Software Technologies, Proceedings. Casimiro, A. & Ferreira, P. M. (eds.). Springer Verlag, p. 53-69 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10873 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Synchronization
Concurrent
Data storage equipment
Labels
High level languages
1
Citation
(Scopus)
Scalability and state: A critical assessment of throughput obtainable on big data streaming frameworks for applications with and without state information
Yang, S., Jeong, Y., Hong, C., Jun, H. & Burgstaller, B., 2018 Jan 1, Euro-Par 2017: Parallel Processing Workshops - Euro-Par 2017 International Workshops. Heras, D. B. & Bouge, L. (eds.). Springer Verlag, p. 141-152 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10659 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Streaming Data
Streaming
Scalability
Throughput
Engines
Dynamically Selective Performance Optimization Method for Mobile 3D Graphics Application with N-Screen Service
Piao, J. C., Cho, C. W., Kim, C. G., Burgstaller, B. & Kim, S-D., 2017 Jun 1, In : Wireless Personal Communications. 94, 3, p. 369-391 23 p.Research output: Contribution to journal › Article
Application programming interfaces (API)
Image quality
Bandwidth
Degradation
Processing
Press / Media
Fantom partners with Yonsei University to drive smart contract development
19/4/11
1 item of media coverage
Press/Media: Press / Media