A PERFORMANCE EVALUATION OF THE NEHALEM QUAD-CORE PROCESSOR FOR SCIENTIFIC COMPUTING
| Autor: | Scott Pakin, Adolfy Hoisie, Michael Lang, Darren J. Kerbyson, José Carlos Sancho, Kevin J. Barker, Kei Davis |
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| Rok vydání: | 2008 |
| Předmět: |
Interconnection
Multi-core processor Hardware_MEMORYSTRUCTURES Computer science Node (networking) Parallel computing ComputerSystemsOrganization_PROCESSORARCHITECTURES Simultaneous multithreading computer.software_genre Memory controller Theoretical Computer Science Computational science Hardware and Architecture Factor (programming language) Scalability Operating system Single-core computer Software computer.programming_language |
| Zdroj: | Parallel Processing Letters. 18:453-469 |
| ISSN: | 1793-642X 0129-6264 |
| Popis: | In this work we present an initial performance evaluation of Intel's latest, second-generation quad-core processor, Nehalem, and provide a comparison to first-generation AMD and Intel quad-core processors Barcelona and Tigerton. Nehalem is the first Intel processor to implement a NUMA architecture incorporating QuickPath Interconnect for interconnecting processors within a node, and the first to incorporate an integrated memory controller. We evaluate the suitability of these processors in quad-socket compute nodes as building blocks for large-scale scientific computing clusters. Our analysis of intra-processor and intra-node scalability of microbenchmarks, and a range of large-scale scientific applications, indicates that quad-core processors can deliver an improvement in performance of up to 4x over a single core depending on the workload being processed. However, scalability can be less when considering a full node. We show that Nehalem outperforms Barcelona on memory-intensive codes by a factor of two for a Nehalem node with 8 cores and a Barcelona node containing 16 cores. Further optimizations are possible with Nehalem, including the use of Simultaneous Multithreading, which improves the performance of some applications by up to 50%. |
| Databáze: | OpenAIRE |
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