SC12 Home > SC12 Schedule > SC12 Presentation - Optimization of Geometric Multigrid for Emerging Multi- and Manycore Processors

SCHEDULE: NOV 10-16, 2012

When viewing the Technical Program schedule, on the far righthand side is a column labeled "PLANNER." Use this planner to build your own schedule. Once you select an event and want to add it to your personal schedule, just click on the calendar icon of your choice (outlook calendar, ical calendar or google calendar) and that event will be stored there. As you select events in this manner, you will have your own schedule to guide you through the week.

Optimization of Geometric Multigrid for Emerging Multi- and Manycore Processors

SESSION: Performance Optimization

EVENT TYPE: Papers

TIME: 2:30PM - 3:00PM

SESSION CHAIR: Padma Raghavan

AUTHOR(S):Samuel W. Williams, Dhiraj D. Kalamkar, Amik Singh, Anand M. Deshpande, Brian Van Straalen, Mikhail Smelyanskiy, Ann Almgren, Pradeep Dubey, John Shalf, Leonid Oliker

ROOM:255-BC

ABSTRACT:
Multigrid methods are widely used to accelerate the convergence of iterative solvers for linear systems. We explore optimization techniques for geometric multigrid on existing and emerging multicore systems including the Cray XE6, Intel SandyBridge and Nehalem-based Infiniband clusters, as well as Intel's forthcoming Knights Corner (KNC) Coprocessor. Our work examines a variety of techniques including communication-aggregation, threaded wavefront-based DRAM communication-avoiding, dynamic threading decisions, SIMDization, and fusion of operators. We quantify performance through each phase of the V-cycle for both single-node and distributed-memory experiments and provide detailed analysis for each class of optimization. Results show our optimizations yield significant speedups across a variety of subdomain sizes while demonstrating the potential of multi- and manycore processors to dramatically accelerate single-node performance. Our analysis also indicates that improvements in networks and communication will be essential to reap the potential of manycore processors in large-scale multigrid simulations.

Chair/Author Details:

Padma Raghavan (Chair) - Pennsylvania State University

Samuel W. Williams - Lawrence Berkeley National Laboratory

Dhiraj D. Kalamkar - Intel Corporation

Amik Singh - University of California, Berkeley

Anand M. Deshpande - Intel Corporation

Brian Van Straalen - Lawrence Berkeley National Laboratory

Mikhail Smelyanskiy - Intel Corporation

Ann Almgren - Lawrence Berkeley National Laboratory

Pradeep Dubey - Intel Corporation

John Shalf - Lawrence Berkeley National Laboratory

Leonid Oliker - Lawrence Berkeley National Laboratory

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar

Optimization of Geometric Multigrid for Emerging Multi- and Manycore Processors

SESSION: Performance Optimization

EVENT TYPE:

TIME: 2:30PM - 3:00PM

SESSION CHAIR: Padma Raghavan

AUTHOR(S):Samuel W. Williams, Dhiraj D. Kalamkar, Amik Singh, Anand M. Deshpande, Brian Van Straalen, Mikhail Smelyanskiy, Ann Almgren, Pradeep Dubey, John Shalf, Leonid Oliker

ROOM:255-BC

ABSTRACT:
Multigrid methods are widely used to accelerate the convergence of iterative solvers for linear systems. We explore optimization techniques for geometric multigrid on existing and emerging multicore systems including the Cray XE6, Intel SandyBridge and Nehalem-based Infiniband clusters, as well as Intel's forthcoming Knights Corner (KNC) Coprocessor. Our work examines a variety of techniques including communication-aggregation, threaded wavefront-based DRAM communication-avoiding, dynamic threading decisions, SIMDization, and fusion of operators. We quantify performance through each phase of the V-cycle for both single-node and distributed-memory experiments and provide detailed analysis for each class of optimization. Results show our optimizations yield significant speedups across a variety of subdomain sizes while demonstrating the potential of multi- and manycore processors to dramatically accelerate single-node performance. Our analysis also indicates that improvements in networks and communication will be essential to reap the potential of manycore processors in large-scale multigrid simulations.

Chair/Author Details:

Padma Raghavan (Chair) - Pennsylvania State University

Samuel W. Williams - Lawrence Berkeley National Laboratory

Dhiraj D. Kalamkar - Intel Corporation

Amik Singh - University of California, Berkeley

Anand M. Deshpande - Intel Corporation

Brian Van Straalen - Lawrence Berkeley National Laboratory

Mikhail Smelyanskiy - Intel Corporation

Ann Almgren - Lawrence Berkeley National Laboratory

Pradeep Dubey - Intel Corporation

John Shalf - Lawrence Berkeley National Laboratory

Leonid Oliker - Lawrence Berkeley National Laboratory

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar