AMGCC15 Program - Revision history

Admin: /* Workshop Program | Workshop Main Page */

2015-09-21T12:05:53Z

‎Workshop Program | Workshop Main Page

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2015-09-21T02:25:04Z

‎Workshop Program | Workshop Main Page

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2015-09-21T02:24:27Z

‎Workshop Program | Workshop Main Page

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2015-09-14T02:57:51Z

‎Workshop Program | Workshop Main Page

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2015-09-14T02:57:09Z

‎Workshop Program | Workshop Main Page

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2015-09-14T02:39:06Z

‎Workshop Program | Workshop Main Page

Admin: /* Invited Talks */

2015-09-14T02:37:55Z

‎Invited Talks

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‎Invited Talks

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‎Workshop Program | Workshop Main Page

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‎Keynotes

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 * '''Time''': 08:30 AM - 06:00 PM (Salon VII)
-This workshop features two keynotes by Dr. Alan Edelman (Massachusetts Institute of Technology) and Dr. Kate Keahey (Argonne National Laboratory/University of Chicago), two invited talks by Dr. Robert Quick (Indiana University) and Dr. Hyeonsang Eom (Seoul National University), and oral presentations of 7 full papers.
+This workshop features two keynotes by Dr. Alan Edelman (Massachusetts Institute of Technology) and Dr. Kate Keahey (Argonne National Laboratory/University of Chicago), two invited talks by Robert Quick (Indiana University) and Dr. Hyeonsang Eom (Seoul National University), and oral presentations of 7 full papers.
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 == Workshop Program | [[AMGCC15|Workshop Main Page]]==
-* '''Location''': Salon VII, Boston Marriott Cambridge, Cambridge, MA, USA
+* '''Location''': Boston Marriott Cambridge, Cambridge, MA, USA
 * '''Date''': September 21 (Monday), 2015
-* '''Time''': 08:30 AM - 06:00 PM
+* '''Time''': 08:30 AM - 06:00 PM (Salon VII)
 This workshop features two keynotes by Dr. Alan Edelman (Massachusetts Institute of Technology) and Dr. Kate Keahey (Argonne National Laboratory/University of Chicago), two invited talks by Dr. Robert Quick (Indiana University) and Dr. Hyeonsang Eom (Seoul National University), and oral presentations of 7 full papers.

@@ Line 1: / Line 1: @@
 == Workshop Program | [[AMGCC15|Workshop Main Page]]==
-* '''Location''': Boston Marriott Cambridge, Cambridge, MA, USA
+* '''Location''': Salon VII, Boston Marriott Cambridge, Cambridge, MA, USA
 * '''Date''': September 21 (Monday), 2015
 * '''Time''': 08:30 AM - 06:00 PM

@@ Line 95: / Line 95: @@
 | width="20%"| Seoul National University
-| rowspan="3"| Jik-Soo Kim
+| rowspan="3"| Yoonhee Kim
 |- align="center"

@@ Line 24: / Line 24: @@
 |- align="center"
-| width="10%"| 09:10 - 09:55
+| width="10%"| 09:10 - 10:00
 | width="40%"| '''Keynote''': Julia: A fresh approach to parallel programming
 | width="20%"| Alan Edelman
@@ Line 32: / Line 32: @@
 |- align="center"
-| width="10%"| 09:55 - 10:40
+| width="10%"| 10:00 - 10:45
 | width="40%"| '''Invited Talk''': Autonomy in the Open Science Grid or Pay No Attention to the Operator Behind the Curtains
 | width="20%"| Robert Quick
@@ Line 38: / Line 38: @@
 |- align="center"
-| 10:40 - 11:00
+| 10:45 - 11:00
 | colspan="4" align="center"| Coffee Break

@@ Line 132: / Line 132: @@
 == Invited Talks ==
-=== How can we allocate “right” resources to virtual machines in virtualized data centers? – Workload-aware hierarchical scheduling with OpenStack ===
+=== Autonomy in the Open Science Grid or Pay No Attention to the Operator Behind the Curtains ===
 ==== Talk Abstract ====
-Data centers have been becoming larger and more heterogeneous, possibly being highly distributed. It is crucial to manage many heterogeneous resources effectively to efficiently and cost-effectivity provide services; it is necessary to allocate “right” resources to Virtual Machines (VMs) in virtualized data centers in order to decrease the cost of the operation while meeting the SLAs (Service Level Agreements) such as guaranteeing the latency requirement. One of the most effective ways to allocate “right” resources to a VM would be to do it considering the characteristics of the VM such as the memory intensiveness of the workload executed in the VM. However, the existing schedulers do not consider these kinds of characteristics, including the NOVA scheduler of OpenStack and DRS (Distributed Resource Scheduler) of VMWare. We propose a workload-ware hierarchical scheduler that schedules VMs on OpenStack clusters of nodes, considering the characteristics of workload executed in the VMs and the hierarchy of the resources to be allocated. Our experimental study shows that our memory-intensiveness-aware scheduler may outperform the default scheduler of OpenStack and DRS as well in terms of throughput and latency.
+The Open Science Grid (OSG) is a distributed computational facility providing resources for High Throughput Computing (HTC) workflows. These resources are located at 125 locations across North America and South America, with minor extensions to Asia, Europe, and Africa. By nature, a distributed computing facility of this extent is a chaotic ecosystem, with scheduled and unscheduled outages, network fluctuations, and resource and policy autonomy. To consolidate this system into a functional operational environment the OSG uses a variety of technical and social techniques. These include central operational services that provide dynamic snapshots of the state of OSG, continuous monitoring and subsequent self-repairing actions, active 24x7 tracking and troubleshooting of critical production issues, automatically managed glide-in based workflows, and high availability operational services. This talk will cover and introduction to the OSG, discussion of the scale and chaotic nature of the environment, and techniques used to provide autonomic  production quality service.
-=== Autonomy in the Open Science Grid or Pay No Attention to the Operator Behind the Curtains ===
+=== How can we allocate “right” resources to virtual machines in virtualized data centers? – Workload-aware hierarchical scheduling with OpenStack ===
 ==== Talk Abstract ====
-The Open Science Grid (OSG) is a distributed computational facility providing resources for High Throughput Computing (HTC) workflows. These resources are located at 125 locations across North America and South America, with minor extensions to Asia, Europe, and Africa. By nature, a distributed computing facility of this extent is a chaotic ecosystem, with scheduled and unscheduled outages, network fluctuations, and resource and policy autonomy. To consolidate this system into a functional operational environment the OSG uses a variety of technical and social techniques. These include central operational services that provide dynamic snapshots of the state of OSG, continuous monitoring and subsequent self-repairing actions, active 24x7 tracking and troubleshooting of critical production issues, automatically managed glide-in based workflows, and high availability operational services. This talk will cover and introduction to the OSG, discussion of the scale and chaotic nature of the environment, and techniques used to provide autonomic  production quality service.
+Data centers have been becoming larger and more heterogeneous, possibly being highly distributed. It is crucial to manage many heterogeneous resources effectively to efficiently and cost-effectivity provide services; it is necessary to allocate “right” resources to Virtual Machines (VMs) in virtualized data centers in order to decrease the cost of the operation while meeting the SLAs (Service Level Agreements) such as guaranteeing the latency requirement. One of the most effective ways to allocate “right” resources to a VM would be to do it considering the characteristics of the VM such as the memory intensiveness of the workload executed in the VM. However, the existing schedulers do not consider these kinds of characteristics, including the NOVA scheduler of OpenStack and DRS (Distributed Resource Scheduler) of VMWare. We propose a workload-ware hierarchical scheduler that schedules VMs on OpenStack clusters of nodes, considering the characteristics of workload executed in the VMs and the hierarchy of the resources to be allocated. Our experimental study shows that our memory-intensiveness-aware scheduler may outperform the default scheduler of OpenStack and DRS as well in terms of throughput and latency.

← Older revision		Revision as of 01:36, 14 September 2015
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	== Invited Talks ==		== Invited Talks ==
		+
		+	=== How can we allocate “right” resources to virtual machines in virtualized data centers? – Workload-aware hierarchical scheduling with OpenStack ===
		+
		+	==== Talk Abstract ====
		+
		+	Data centers have been becoming larger and more heterogeneous, possibly being highly distributed. It is crucial to manage many heterogeneous resources effectively to efficiently and cost-effectivity provide services; it is necessary to allocate “right” resources to Virtual Machines (VMs) in virtualized data centers in order to decrease the cost of the operation while meeting the SLAs (Service Level Agreements) such as guaranteeing the latency requirement. One of the most effective ways to allocate “right” resources to a VM would be to do it considering the characteristics of the VM such as the memory intensiveness of the workload executed in the VM. However, the existing schedulers do not consider these kinds of characteristics, including the NOVA scheduler of OpenStack and DRS (Distributed Resource Scheduler) of VMWare. We propose a workload-ware hierarchical scheduler that schedules VMs on OpenStack clusters of nodes, considering the characteristics of workload executed in the VMs and the hierarchy of the resources to be allocated. Our experimental study shows that our memory-intensiveness-aware scheduler may outperform the default scheduler of OpenStack and DRS as well in terms of throughput and latency.

	=== Autonomy in the Open Science Grid or Pay No Attention to the Operator Behind the Curtains ===		=== Autonomy in the Open Science Grid or Pay No Attention to the Operator Behind the Curtains ===

@@ Line 5: / Line 5: @@
 * '''Time''': 08:30 AM - 06:00 PM
 This workshop features two keynotes by Dr. Alan Edelman (Massachusetts Institute of Technology) and Dr. Kate Keahey (Argonne National Laboratory/University of Chicago), two invited talks by Dr. Robert Quick (Indiana University) and Dr. Hyeonsang Eom (Seoul National University), and oral presentations of 7 full papers.
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@@ Line 93: / Line 91: @@
 |- align="center"
 | width="10%"| 16:00 - 16:45
-| width="40%"| '''Invited Talk''': TBD
+| width="40%"| '''Invited Talk''': How can we allocate “right” resources to virtual machines in virtualized data centers? – Workload-aware hierarchical scheduling with OpenStack
-| width="20%"| TBD
+| width="20%"| Hyeonsang Eom
-| width="20%"| TBD
+| width="20%"| Seoul National University
 | rowspan="3"| Jaehwan Lee

@@ Line 118: / Line 118: @@
 == Keynotes ==
-=== Chameleon: A Large-scale, Reconfigurable Experimental Environment for Next Generation Cloud Research ===
+=== Julia: A fresh approach to parallel programming ===
 ==== Talk Abstract ====