{"id":1238,"date":"2023-12-21T18:37:02","date_gmt":"2023-12-21T09:37:02","guid":{"rendered":"https:\/\/css.or.kr\/csc2024\/?page_id=1238"},"modified":"2024-01-24T18:14:26","modified_gmt":"2024-01-24T09:14:26","slug":"%ed%94%84%eb%a1%9c%ea%b7%b8%eb%9e%a8","status":"publish","type":"page","link":"https:\/\/css.or.kr\/csc2024\/?page_id=1238","title":{"rendered":"\ud504\ub85c\uadf8\ub7a8"},"content":{"rendered":"\n

\ub2e4\uc6b4\ub85c\ub4dc:<\/strong> \ud504\ub85c\uc2dc\ub529<\/a><\/p>\n\n\n\n

1\uc6d4 22\uc77c \uc6d4\uc694\uc77c<\/h2>\n\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\t
\uc2dc\uac04<\/strong><\/td>\n \ud504\ub85c\uadf8\ub7a8<\/strong><\/td>\n <\/tr>\n \n
12:30-12:35<\/strong><\/td>\n \uac1c\ud68c\uc2dd<\/b><\/td>\n <\/tr>\n \n
12:35-13:20<\/strong><\/td>\n \n Keynote Speech 1<\/b>\n
\uc0ac\ud68c: \uad8c\uc601\uc9c4 \uad50\uc218(KAIST)<\/div>\n <\/td>\n <\/tr>\n
\n \uc0c8\ub85c\uc6b4 \uace0\ub4f1\uad50\uc721 \ud328\ub7ec\ub2e4\uc784(Online)\n\t
\ucd5c\uc591\ud76c \ud55c\ub9bc\ub300\ud559\uad50 \ucd1d\uc7a5(\u524d \ubbf8\ub798\ucc3d\uc870\uacfc\ud559\ubd80 \uc7a5\uad00)<\/div>\n <\/td>\n <\/tr>\n \n
13:20-14:50<\/strong><\/td>\n \n S1: System Hardware<\/b>\n
\uc88c\uc7a5: \ubc15\uc601\uc900 \uad50\uc218(\uc5f0\uc138\ub300\ud559\uad50)<\/div><\/td>\n <\/tr>\n
\n\tAccelerators for Bootstrappable Fully Homomorphic Encryption\n\t
\uc548\uc815\ud638 \uad50\uc218(\uc11c\uc6b8\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n\tHouse of Cards in Distributed Training Systems\n\t
\uae40\ub3d9\uc900 \uad50\uc218(KAIST)<\/div>\n <\/td>\n <\/tr>\n
\n\tCase for DRAM Translation Layer (DTL): It’s like FTL but for (CXL) DRAM!\n\t
\uc774\uc7ac\uc6b1 \uad50\uc218(\uc11c\uc6b8\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n \n
14:50-15:00<\/strong><\/td>\n \ud64d\ubcf4\uc138\uc158: \ub9ac\ubca8\ub9ac\uc628<\/strong><\/td>\n <\/tr>\n \n
15:00-15:20<\/strong><\/td>\n Coffee Break<\/strong><\/td>\n <\/tr>\n \n
15:20-17:20<\/strong><\/td>\n \n S2: System Software <\/b>\n\t
\uc88c\uc7a5: \uc774\uc601\ubbfc \uad50\uc218(\uc11c\uc6b8\uc2dc\ub9bd\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n Serving DNNs on GPU Servers in the Face of Cold Starts\n\t
\uc548\uc815\uc12d \uad50\uc218(\uc544\uc8fc\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n Scheduling Optimizations for Neural Network Training and Inference\n
\uc11c\uc9c0\uc6d0 \uad50\uc218(\ud55c\uc591\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n Performance Enhancement of Memory Disaggregation in Elastic Memory Platform (EMP)\n
\uae40\ucc3d\ub300 \uc5f0\uad6c\uc6d0(ETRI) <\/div>\n <\/td>\n <\/tr>\n
\n WebOS TV \uc2dc\uc2a4\ud15c \uc131\ub2a5 \uac1c\uc120 \uc0ac\ub840\ub85c \ubcf4\ub294 \uc784\ubca0\ub514\ub4dc \uc2dc\uc2a4\ud15c\uc5d0\uc11c\uc758 \uc624\ud508\uc18c\uc2a4 \uc801\uc6a9 \ucd5c\uc801\ud654\n
\ubbfc\uad6c\ubd09 \uc2e4\uc7a5(LG\uc804\uc790) <\/div>\n <\/td>\n <\/tr>\n \n
17:20-18:40<\/strong><\/td>\n \n \ud559\uc0dd\uad50\ub958 \ud504\ub85c\uadf8\ub7a8<\/b>\n\t
\uc9c4\ud589: \uae40\uc6b1\ud76c \uad50\uc218(\uac74\uad6d\ub300\ud559\uad50), \ubb38\ud604\uace4 \uad50\uc218(UNIST)<\/div>\n <\/td>\n <\/tr>\n
\ud3ec\uc2a4\ud130<\/td>\n <\/tr>\n \n
19:00-20:30<\/strong><\/td>\n\tBanquet<\/strong><\/td>\n <\/tr>\n <\/tbody>\n<\/table>\n\n\n\n

1\uc6d4 23\uc77c \ud654\uc694\uc77c<\/h2>\n\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
\uc2dc\uac04<\/strong><\/td>\n \ud504\ub85c\uadf8\ub7a8<\/strong><\/td>\n <\/tr>\n \n
09:00-10:40<\/strong><\/td>\n \n S3: Newcomers <\/b>\n\t
\uc88c\uc7a5: \uad6c\uac74\uc7ac \uad50\uc218(\uace0\ub824\ub300\ud559\uad50)<\/div><\/td>\n <\/tr>\n
\n\tSystems for Tiny Machine Learning\n\t
\ud5c8\uc120\uc601 \uad50\uc218(\uacbd\ud76c\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n\tDatabase Systems for ML Prediction\n\t
\ubc15\uad11\ud604 \uad50\uc218(\uc5f0\uc138\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n\tResearch on Deep Learning Clouds: A Predictive Approach\n\t
\uc591\uacbd\uc2dd \uad50\uc218(\uace0\ub824\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n\tFinding Browser Bugs in Content Security Policy Enforcement through Differential Testing\n\t
\uc704\uc131\uc77c \uad50\uc218(UNIST)<\/div>\n <\/td>\n <\/tr>\n \n
10:40-11:00<\/strong><\/td>\n Coffee Break<\/strong><\/td>\n <\/tr>\n \n
11:00-11:45<\/strong><\/td>\n \n Keynote Speech 2<\/b>\n
\uc0ac\ud68c: \ud0c1\ubcd1\ucca0 \uad50\uc218(\uacbd\ubd81\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n Adversarial Machine Learning and \ba Few Systematic Approaches for Defense\n\t
\uae40 \uc885 \uad50\uc218(POSTECH)<\/div>\n <\/td>\n <\/tr>\n \n
11:45-13:20<\/strong><\/td>\n Lunch Break<\/strong><\/td>\n <\/tr>\n \n
13:20-15:20<\/strong><\/td>\n \n S4: Large Language Model<\/b>\n\t
\uc88c\uc7a5: \uc804\uba85\uc7ac \uad50\uc218(UNIST)<\/div>\n <\/td>\n <\/tr>\n
\n Systems for Fast Training of Large Language Models\n\t
\uc774\uc9c4\ud638 \uad50\uc218(\uc11c\uc6b8\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n Unlocking Efficiency in LLMs: The Role of Model Compression\n
\uad8c\uc138\uc911 \ub9ac\ub354(\ub124\uc774\ubc84) <\/div>\n <\/td>\n <\/tr>\n
\n Machine Learning Force Field (MLFF) Accelerating Large Simulation with Machine Learning\n
\uc774\uc2b9\uc6d0 \ub9c8\uc2a4\ud130(\uc0bc\uc131 SAIT) <\/div>\n <\/td>\n <\/tr>\n
\n Recent Advances in Large Language Models\n
\uc774\ubb38\ud0dc \uad50\uc218\/\ub7a9\uc7a5(UIC\/LG AI\uc5f0\uad6c\uc18c)<\/div>\n <\/td>\n <\/tr>\n \n
15:20-15:50<\/strong><\/td>\n Coffee Break<\/b><\/td>\n <\/tr>\n \n
15:50-17:50<\/strong><\/td>\n \n S5: Processing in Memory<\/b>\n\t
\uc88c\uc7a5: \uae40\ud55c\uc900 \uad50\uc218(\uc5f0\uc138\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n\tPID-Join: Accelerating In-Memory Joins by Leveraging Processing-in-DIMM on Commodity DIMMs\n\t
\uae40\uc601\uc11d \uad50\uc218(\uc5f0\uc138\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n\tSamsung PIM\/PNM for LLM\n\t
\uc720\uc7ac\ud6c8 \ub9c8\uc2a4\ud130(\uc0bc\uc131 SAIT)<\/div>\n <\/td>\n <\/tr>\n
\n\tEfficient Execution of Multiple PIM Applications on a Shared PIM Architecture\n\t
\ubc15\uc601\uc900 \uad50\uc218(\uc5f0\uc138\ub300\ud559\uad50)<\/div>\n <\/td>\n <\/tr>\n
\n\tCXL-based Memory-centric Computing: Case Studies for Data Analytics and AI Service Platform\n\t
\uc2e0\uad11\uc2dd \ud300\uc7a5(SK Hynix)<\/div>\n <\/td>\n <\/tr>\n <\/tbody>\n<\/table>\n\n\n\n

1\uc6d4 24\uc77c \uc218\uc694\uc77c<\/h2>\n\n\n\n\n \n \n \n \n
\uc2dc\uac04<\/strong><\/td>\n \ud504\ub85c\uadf8\ub7a8<\/strong><\/td>\n <\/tr>\n \n
09:00-11:05<\/strong><\/td>\n \n \uc790\uc720\ud1a0\ub860: \ubbf8\ub798\uc18c\ud504\ud2b8\uc6e8\uc5b4 \uc815\ucc45 \ud559\uc220 \ud1a0\ub860<\/b>\n
\uc0ac\ud68c: \ud0c1\ubcd1\ucca0 \uad50\uc218(\uacbd\ubd81\ub300\ud559\uad50), \uad8c\uc601\uc9c4 \uad50\uc218(KAIST)<\/div>\n <\/td>\n <\/tr>\n \n
11:00<\/strong><\/td>\n \ud3d0\ud68c\uc2dd<\/b><\/td>\n <\/tr>\n <\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

\ub2e4\uc6b4\ub85c\ub4dc: \ud504\ub85c\uc2dc\ub529 1\uc6d4 22\uc77c \uc6d4\uc694\uc77c \uc2dc\uac04 \ud504\ub85c\uadf8\ub7a8 12:30-12:35 \uac1c\ud68c\uc2dd 12:35-13:20 Keynote Speech 1 \uc0ac\ud68c: \uad8c\uc601\uc9c4 \uad50\uc218(KAIST) \uc0c8\ub85c\uc6b4 \uace0\ub4f1\uad50\uc721 \ud328\ub7ec\ub2e4\uc784(Online) \ucd5c\uc591\ud76c \ud55c\ub9bc\ub300\ud559\uad50 \ucd1d\uc7a5(\u524d \ubbf8\ub798\ucc3d\uc870\uacfc\ud559\ubd80 \uc7a5\uad00) 13:20-14:50 S1: System Hardware \uc88c\uc7a5: \ubc15\uc601\uc900 \uad50\uc218(\uc5f0\uc138\ub300\ud559\uad50) Accelerators for Bootstrappable Fully Homomorphic Encryption \uc548\uc815\ud638 \uad50\uc218(\uc11c\uc6b8\ub300\ud559\uad50) House of Cards in Distributed Training Systems \uae40\ub3d9\uc900 \uad50\uc218(KAIST) Case for DRAM Translation Layer (DTL): It’s Read More …<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1238","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/css.or.kr\/csc2024\/index.php?rest_route=\/wp\/v2\/pages\/1238","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/css.or.kr\/csc2024\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/css.or.kr\/csc2024\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/css.or.kr\/csc2024\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/css.or.kr\/csc2024\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1238"}],"version-history":[{"count":67,"href":"https:\/\/css.or.kr\/csc2024\/index.php?rest_route=\/wp\/v2\/pages\/1238\/revisions"}],"predecessor-version":[{"id":1425,"href":"https:\/\/css.or.kr\/csc2024\/index.php?rest_route=\/wp\/v2\/pages\/1238\/revisions\/1425"}],"wp:attachment":[{"href":"https:\/\/css.or.kr\/csc2024\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1238"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}