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    114.   1112
    Track > Session : Analytics & Intelligence > Real-time Analytics
    ¹ßÇ¥Á¦¸ñ : °í¼Ó Åë½Å ÆÐŶ ÀúÀå ¹× ºÐ¼®À» À§ÇÑ ½Ã°è¿­ µ¥ÀÌÅͺ£À̽ºÀÇ È°¿ë
    ¹ßÇ¥ÀÚ : ±è¼ºÁø (´ëÇ¥ÀÌ»ç/¢ßÀÎÇÇ´ÏÇ÷°½º)
    °­¿¬¿ä¾à :  ÀüÅëÀûÀÎ Æ®·£Àè¼Ç ±â¹Ý DBMSÀÇ Æ¯Â¡À» ¼Ò°³  ½Ç½Ã°£ ÆÐŶ ÀúÀå ¹× ºÐ¼®À» À§ÇÑ ±â¼úÀû ¿ä±¸ »çÇ×À» ¼Ò°³ÇÏ°í, ÀüÅëÀû ¼Ö·ç¼ÇÀ» ÅëÇÑ ±â¼ú ÇÑ°è ±â¼ú  ½Ç½Ã°£ µ¥ÀÌÅÍ ºÐ¼®À» À§ÇÑ ½Å°³³ä ½Ã°è¿­ µ¥ÀÌÅͺ£À̽º ¼Ò°³  °í¼º´É µ¥ÀÌÅÍ Ã³¸®¸¦ À§ÇÑ ½Å±â¼ú ¼Ò°³  ÆÐŶ ºÐ¼® ¹× È°...more
    Track > Session : Analytics & Intelligence > Real-time Analytics
    ¹ßÇ¥Á¦¸ñ : High-Productivity Big Data Analytics with SparkR
    ¹ßÇ¥ÀÚ : Á¤»ó¿À (¸Å´ÏÀú/SKT)
    °­¿¬¿ä¾à : RÀº ¿ÀǼҽº ±â¹ÝÀÇ Åë°èÀû 󸮸¦ À§ÇÑ ÇÁ·Î±×·¡¹Ö ¾ð¾î·Î¼­, ´Ù¾çÇÑ ÆÐÅ°ÁöµéÀ» °¡Áö°í ÀÖ°í, µ¥ÀÌÅÍ ºÐ¼®À» À§ÇØ ±× »ç¿ëÀÌ Áõ°¡ÇÏ°í ÀÖ´Ù. ±×·±µ¥, ÇöÀçÀÇ RÀº Single machine¿¡¼­¸¸ µ¥ÀÌÅÍ Ã³¸®°¡ °¡´ÉÇϱ⠶§¹®¿¡, ºòµ¥ÀÌÅÍ Ã³¸®¿¡´Â ÀûÇÕÇÏÁö ¾Ê´Ù. ÃÖ±Ù ±âÁ¸ÀÇ Hadoop ±â¹ÝÀÇ ºÐ»êó¸® ½Ã½ºÅÛº¸´Ù ºü¸¥ SparkÀ̶ó...more
    Track > Session : Analytics & Intelligence > Deep Learning and Internet
    ¹ßÇ¥Á¦¸ñ : Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multipl...
    ¹ßÇ¥ÀÚ : ±è°ÇÈñ (±³¼ö/¼­¿ï´ëÇб³)
    °­¿¬¿ä¾à : In this talk, I will introduce Poseidon, a scalable system architecture for distributed inter-machine communication in existing deep learning frameworks. Poseidon features three key contributions: (1) a three-level hybrid architecture that allows Poseidon to support both CPU-only and GPU-equipped cl...more
    Track > Session : Analytics & Intelligence > Deep Learning and Internet
    ¹ßÇ¥Á¦¸ñ : DeepSpark: Spark-Based Deep Learning Supporting Asynchronous Updates and Caffe C...
    ¹ßÇ¥ÀÚ : À±¼º·Î (±³¼ö/¼­¿ï´ë)
    °­¿¬¿ä¾à : The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large-scale data processing pipelines for handling massive data and parameters involved in DNN training. Distributed computing platforms and GPGPU-based acceleration provide a mainstream solution to ...more
    Track > Session : Analytics & Intelligence > Deep Learning and Internet
    ¹ßÇ¥Á¦¸ñ : Learning-leveraged Intelligent Cloud Platform for IoT Services
    ¹ßÇ¥ÀÚ : ÀÌ¿ø¼® (»ó¹«/»ï¼ºÀüÀÚ)
    °­¿¬¿ä¾à : The Internet of Things (IoT) is taking a center stage of industry and academia. In the history of IT, IoT becomes one of the most interesting technical fields to participate and watch as engineers and users. From engineering standpoints, device connectivity, data storage, and computation including c...more
    Track > Session : Tutorials for Basics > Linux Kernel & Networking
    ¹ßÇ¥Á¦¸ñ : Linux Kernel °³¹ß µ¿Çâ
    ¹ßÇ¥ÀÚ : ±è³²Çü (¼±ÀÓ¿¬±¸¿ø/LGÀüÀÚ)
    °­¿¬¿ä¾à : ÃÖ±Ù ¸®´ª½º Ä¿³ÎÀÇ °³¹ß ¹æÇâ°ú ÃÖ±Ù ÁÖ¿ä º¯°æ »çÇ׿¡ ´ëÇؼ­ »ìÆ캾´Ï´Ù. - Cgroup - Namespace - Various(networking) improvementsmore
    Track > Session : Tutorials for Basics > Linux Kernel & Networking
    ¹ßÇ¥Á¦¸ñ : Linux ³×Æ®¿öÅ· ¿ø¸®¿Í SDN
    ¹ßÇ¥ÀÚ : °ø¿ëÁØ (¼¿Àå/Ä«Ä«¿À)
    °­¿¬¿ä¾à : ¸®´ª½º Ä¿³ÎÀÇ socket buffer ½ºÆ®·°Ã³(skb)¸¦ ±â¹ÝÀ¸·Î ÇÏ´Â ¼­¹ö »çÀÌµå ³×Æ®¿öÅ©ÀÇ ¿ø¸®¿¡ ´ëÇؼ­ À̾߱â ÇÑ´Ù. L2/L3 overlay full-mesh ±â¹ÝÀÇ ³×Æ®¿öÅ©°¡ °¡Áö°í ÀÖ´Â È®À强 À̽´¿¡ ´ëÇؼ­ ¼³¸íÇϸç, À̸¦ ÇÇÇØ°¡±â À§ÇÑ »õ·Î¿î ³×Æ®¿öÅ© ¸ðµ¨°ú ¿ÀǽºÅÃÀÇ ´ºÆ®·ÐÀ» »ç¿ëÇÑ Àû¿ë ¹æ½Ä¿¡ ´ëÇؼ­ ¼³¸íÇÑ´Ù. ÀÌ°ÍÀ» ±â...more
    Track > Session : Tutorials for Basics > SDN/NFV/Cloud Basics
    ¹ßÇ¥Á¦¸ñ : NFV ±âº»°ú OPNFV ÇÁ·ÎÁ§Æ® ÇöȲ
    ¹ßÇ¥ÀÚ : ¹Úµ¿ÁÖ (Technical Director/¿¡¸¯½¼¿¤Áö)
    °­¿¬¿ä¾à : SDN/NFV/Cloud´Â 5G¿Í ÇÔ²² ³×Æ®¿öÅ©ÀÇ ¹ßÀü ¹æÇâÀ¸·Î Àνĵǰí ÀÖ´Ù. º» °­¿¬¿¡¼­´Â SDN/NFV/CloudÀÇ Àü¹ÝÀûÀÎ µ¿ÇâÀ» »ìÆ캸°í ±× Áß ÃÖ±Ù °¡Àå °ü½ÉÀ» ¸¹ÀÌ ¹Þ°í ÀÖ´Â open source projectÀÎ OPNFV¿¡ ´ëÇØ ¾Ë¾Æº»´Ù. OPNFV´Â ±âÁ¸ÀÇ open source project »Ó ¾Æ´Ï¶ó Ç¥ÁØ°ú ½ÃÀåÀ» ¿¬°áÇÏ´Â Áß¿äÇÑ ¿¬°á°í¸®·Î È°µ¿ÇÏ°í...more
    Track > Session : Tutorials for Basics > HPC/BigData Basics
    ¹ßÇ¥Á¦¸ñ : BigData ±âº» ¹× µ¿Çâ
    ¹ßÇ¥ÀÚ : ÃÖ¿µ¸® (±³¼ö/¿ï»ê°úÇбâ¼ú¿ø)
    °­¿¬¿ä¾à : ÃÖ±Ù µé¾î ºòµ¥ÀÌÅÍ Ã³¸®¿¡ À־ ¼º´É Çâ»óÀ» À§ÇØ Àθ޸𸮰¡ ¸¹ÀÌ »ç¿ëµÇ´Â Ãß¼¼ÀÌ´Ù. Àθ޸𸮠±â¹Ý ºòµ¥ÀÌÅÍ Ã³¸® ±â¼úÀ» ¼Ò°³ÇÏ°í ÃÖ±Ù ¿¬±¸ µ¿Çâ¿¡ ´ëÇؼ­ À̾߱âÇÑ´Ù.more
    Track > Session : Tutorials for Basics > HPC/BigData Basics
    ¹ßÇ¥Á¦¸ñ : HPC ±âº» ¹× µ¿Çâ
    ¹ßÇ¥ÀÚ : ³²´öÀ± (½ÇÀå/Çѱ¹°úÇбâ¼úÁ¤º¸¿¬±¸¿ø (KISTI))
    °­¿¬¿ä¾à : ½´ÆÛÄÄÇ»ÅÍ ¿î¿ë¿¡ À־ Àü·Â °¡°ÝÀÇ »ó½ÂÀ¸·Î ¿î¿µºñ´Â ´õ¿í ºÎ´ãÀÌ µÇ´Â »óȲÀ̸ç, ÇöÀç ´ë´Ù¼öÀÇ ½´ÆÛÄÄÇ»ÅÍ ±¸Ãà ¹æ½ÄÀΠŬ·¯½ºÅÍ ¹æ½ÄÀÇ °æ¿ì °í¼º´É ÄÄÇ»Å͸¦ ±¸ÃàÇϱâ À§Çؼ­´Â ´ë±Ô¸ðÀÇ ºÎÁö°¡ ÇÊ¿äÇÏ´Ù. ÇâÈÄ 5³â ³»¿¡ ÇöÀç Æ䟽ºÄÉÀÏ ¼öÁØÀÇ ÄÄÇ»Æà ¼º´ÉÀÌ ¿¢»ç½ºÄÉÀÏ ¼öÁرîÁö ¹ßÀüÇÒ °ÍÀ̸ç, ¿¢»ç½ºÄÉÀÏ ½´...more
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