| Achieving a single compute device image in OpenCL for multiple GPUs J Kim, H Kim, JH Lee, J Lee ACM Sigplan Notices 46 (8), 277-288, 2011 | 186 | 2011 |
| BSSync: Processing near memory for machine learning workloads with bounded staleness consistency models JH Lee, J Sim, H Kim 2015 International Conference on Parallel Architecture and Compilation (PACT …, 2015 | 80 | 2015 |
| SmartSSD: FPGA accelerated near-storage data analytics on SSD JH Lee, H Zhang, V Lagrange, P Krishnamoorthy, X Zhao, YS Ki IEEE Computer architecture letters 19 (2), 110-113, 2020 | 62 | 2020 |
| GPUMech: GPU performance modeling technique based on interval analysis JC Huang, JH Lee, H Kim, HHS Lee 2014 47th Annual IEEE/ACM International Symposium on Microarchitecture, 268-279, 2014 | 60 | 2014 |
| NASCENT: Near-storage acceleration of database sort on SmartSSD S Salamat, A Haj Aboutalebi, B Khaleghi, JH Lee, YS Ki, T Rosing The 2021 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays …, 2021 | 39 | 2021 |
| OpenCL performance evaluation on modern multicore CPUs JH Lee, N Nigania, H Kim, K Patel, H Kim Scientific Programming 2015, 4-4, 2016 | 38 | 2016 |
| Java In Client Ahead-Of-Time Compiler for Embedded System S Hong, JC Kim, JW Shin, JW Kwon, JH Lee, SM Moon. 한국정보과학회 학술발표논문집 36 (2A), 226-227, 2009 | 32 | 2009 |
| On the limits of parallelizing convolutional neural networks on gpus B Pourghassemi, C Zhang, JH Lee, A Chandramowlishwaran Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and …, 2020 | 12* | 2020 |
| Web browsing apparatus and method through storing and optimizing JAVASCRIPT® code JH Lee, H Kim, G Jo, J Nah, H Kim, YJ Lee, J Lee, SM Cho US Patent 8,887,127, 2014 | 10 | 2014 |
| FPGA acceleration system for MSR codes M Qin, JH Lee, R Pitchumani, YS Ki US Patent 11,061,772, 2021 | 5 | 2021 |
| Optimal dynamic shard creation in storage for graph workloads SH Hashemi, JH Lee, YS KI US Patent App. 16/274,232, 2020 | 4 | 2020 |
| StaleLearn: Learning acceleration with asynchronous synchronization between model replicas on PIM JH Lee, H Kim IEEE Transactions on Computers 67 (6), 861-873, 2017 | 4 | 2017 |
| SESH framework: A space exploration framework for GPU application and hardware codesign JH Lee, J Meng, H Kim High Performance Computing Systems. Performance Modeling, Benchmarking and …, 2014 | 4 | 2014 |
| Near-storage acceleration of dictionary decoding S Salamat, JH Lee, AHAJ ABOUTALEBI, P Krishnamoorthy, X Zhao, ... US Patent 11,791,838, 2023 | 3 | 2023 |
| Slab based memory management for machine learning training JH Lee, YS Ki US Patent 11,461,869, 2022 | 3 | 2022 |
| Systems, methods, and devices for storage shuffle acceleration H Zhang, JH Lee, Y Zhang, AHAJ ABOUTALEBI, X Zhao, ... US Patent 11,567,971, 2023 | 2 | 2023 |
| Memory management for machine learning training on GPU JH Lee, YS Ki US Patent 11,468,312, 2022 | 2 | 2022 |
| Empirical Investigation of Stale Value Tolerance on Parallel RNN Training JH Lee, H Kim 2019 IEEE International Symposium on Performance Analysis of Systems and …, 2019 | 2 | 2019 |
| Measuring JavaScript Performance with a Real World Web Application H Kim, JH Lee, G Jo, J Lee 한국정보과학회 학술발표논문집 38 (2A), 131-134, 2011 | 2 | 2011 |
| Platform for concurrent execution of GPU operations BP Najafabadi, JH Lee, YS Ki US Patent 11,620,510, 2023 | 1 | 2023 |
Hyesoon KimGeorgia TechVerified email at cc.gatech.edu
