BEGIN:VCALENDAR
PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
BEGIN:VEVENT
DTSTART:20121114T003000Z
DTEND:20121114T020000Z
LOCATION:251-F
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: Hadoop MapReduce and High Performance Computing share many characteristics such as, large data volumes, variety of data types, distributed system architecture, required linear performance growth with scalable deployment and high CPU utilization. RDMA capable programing models enable efficient data transfers between computation nodes. In this session we will discuss a collaborative work done among several industry and academic partners on porting Hadoop MapReduce framework to RDMA, the challenges, the techniques used, the benchmarking and testing.
SUMMARY:High Performance Computing Programing Techniques For Big Data Hadoop
PRIORITY:3
END:VEVENT
END:VCALENDAR
BEGIN:VCALENDAR
PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
BEGIN:VEVENT
DTSTART:20121114T003000Z
DTEND:20121114T020000Z
LOCATION:251-F
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: Hadoop MapReduce and High Performance Computing share many characteristics such as, large data volumes, variety of data types, distributed system architecture, required linear performance growth with scalable deployment and high CPU utilization. RDMA capable programing models enable efficient data transfers between computation nodes. In this session we will discuss a collaborative work done among several industry and academic partners on porting Hadoop MapReduce framework to RDMA, the challenges, the techniques used, the benchmarking and testing.
SUMMARY:High Performance Computing Programing Techniques For Big Data Hadoop
PRIORITY:3
END:VEVENT
END:VCALENDAR