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  1. Proceedings of the twelfth ACM SIGPLAN workshop on Erlang (Erlang '13)
  2. Actor scheduling for multicore hierarchical memory platforms
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ACM SIGPLAN Erlang workshop 2013: keynote
Using many-core coprocessor to boost up Erlang VM
Software agents mobility using process migration mechanism in distributed Erlang
Scalable persistent storage for Erlang: theory and practice
Turning web services descriptions into quickcheck models for automatic testing
On the scalability of the Erlang term storage
Actor scheduling for multicore hierarchical memory platforms
Towards an abstraction for remote evaluation in Erlang
Testing blocking operations with QuickCheck's component library
Riak PG: distributed process groups on dynamo-style distributed storage
Extending Erlang by utilising RefactorErl
Towards property-based testing of RESTful web services
Multicore profiling for Erlang programs using percept2

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Actor scheduling for multicore hierarchical memory platforms

Content Provider ACM Digital Library
Author Francesquini, Emilio Goldman, Alfredo Méhaut, Jean-François
Abstract Erlang applications are present in several mission-critical systems. These systems demand substantial computing resources that are usually provided by multiprocessor and multi-core platforms. Hierarchical memory platforms, or Non-Uniform Memory Access (NUMA) architectures, account for an important share of these platforms. Yet, the research on the suitability of the current virtual machine (VM) for these platforms is quite limited. The current VM assumes a flat memory space, thus not performing as well as it could on these architectures. The NUMA environment presents challenges to the runtime environment in fields varying from memory management to scheduling and load-balancing. In this article we summarize some of the characteristics of an actor based application to, in light of the above, introduce some NUMA-aware improvements to the Erlang VM. This modified VM uses the NUMA characteristics and the application knowledge to take better memory management, scheduling and load-balancing decisions. We show that, when we consider the default Erlang VM as the baseline, the modified VM can achieve performance improvements up to a factor of 2.50 while limiting the slowdown on the worst case by a factor of 1.15.
Starting Page 51
Ending Page 62
Page Count 12
File Format PDF
ISBN 9781450323857
DOI 10.1145/2505305.2505313
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2013-09-28
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Profiling Multi-core Pinning Actor model Erlang Numa
Content Type Text
Resource Type Article
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