Chang Bae

dblp:40/7803 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 62% Energy-efficient computing · 19% Memory systems · 19%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing
virtualization
0.112012
Dynamic adaptive virtual core mapping to improve power, energy, and performance in multi-socket multicores · HPDC 2012
Memory systems
memory referencing behavior
0.012012
Dynamic adaptive virtual core mapping to improve power, energy, and performance in multi-socket multicores · HPDC 2012
Energy-efficient computing
power management
0.012012
Dynamic adaptive virtual core mapping to improve power, energy, and performance in multi-socket multicores · HPDC 2012

Methods — techniques the papers use, named apart from their topics

online policy · 0.1dynamic migration · 0.1
YearPublicationVenuePosition
2012 Dynamic adaptive virtual core mapping to improve power, energy, and performance in multi-socket multicores
abstract
Consider a multithreaded parallel application running inside a multicore virtual machine context that is itself hosted on a multi-socket multicore physical machine. How should the VMM map virtual cores to physical cores? We compare a local mapping, which compacts virtual cores to processor sockets, and an interleaved mapping, which spreads them over the sockets. Simply choosing between these two mappings exposes clear tradeoffs between performance, energy, and power. We then describe the design, implementation, and evaluation of a system that automatically and dynamically chooses between the two mappings. The system consists of a set of efficient online VMM-based mechanisms and policies that (a) capture the relevant characteristics of memory reference behavior, (b) provide a policy and mechanism for configuring the mapping of virtual machine cores to physical cores that optimizes for power, energy, or performance, and (c) drive dynamic migrations of virtual cores among local physical cores based on the workload and the currently specified objective. Using these techniques we demonstrate that the performance of SPEC and PARSEC benchmarks can be increased by as much as 66%, energy reduced by as much as 31%, and power reduced by as much as 17%, depending on the optimization objective.
Chang Bae, Lei Xia 0001, Peter A. Dinda, Jack Lange
HPDC1
2011 Minimal-overhead virtualization of a large scale supercomputer
abstract
Virtualization has the potential to dramatically increase the usability and reliability of high performance computing (HPC) systems. However, this potential will remain unrealized unless overheads can be minimized. This is particularly challenging on large scale machines that run carefully crafted HPC OSes supporting tightly-coupled, parallel applications. In this paper, we show how careful use of hardware and VMM features enables the virtualization of a large-scale HPC system, specifically a Cray XT4 machine, with < = 5% overhead on key HPC applications, microbenchmarks, and guests at scales of up to 4096 nodes. We describe three techniques essential for achieving such low overhead: passthrough I/O, workload-sensitive selection of paging mechanisms, and carefully controlled preemption. These techniques are forms of symbiotic virtualization, an approach on which we elaborate.
Jack Lange, Kevin T. Pedretti, Peter A. Dinda, Patrick G. Bridges, Chang Bae, Philip Soltero, Alex Merritt
VEE5