Architecture of Computing Systems (Lecture Notes in Computer ...

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146 Y. Liu et al. 5.2 Results and Analysis The speedup of CPR scheme over original flattening model is shown in Fig. 4, in which Fig. 4(a) shows the relationship between speedup and number of nesting levels, while Fig. 4(b) shows the relationship between speedup and density of data sharing among nesting levels. As Fig. 4(a) shows, the speedup is approximate to 1 when nesting levels is 1, at this time, the CPR scheme equals to the flattening model. The speedup value increases with the increasing of nesting levels and processors. It reaches 2.8 for 4 nesting levels and 16 processors. The reason is that the more nesting levels Speedup over flattening model Speedup over flattening model 3 2.5 2 1.5 1 nest-1 nest-2 nest-3 nest-4 0.5 2 4 8 16 Number of Processors (a) Speedup of different nesting levels 3 2.5 2 1.5 1 share-h share-m share-n 0.5 2 4 8 16 Number of Processors (b) Speedup of different densities of data sharing Fig. 4. Speedup of CPR over flattening model
Efficient Transaction Nesting in Hardware Transactional Memory 147 the transactions have, the bigger the difference is between partial rollback and rolling back to the outermost transaction, and furthermore, the probability of conflict increases with the increasing of processors due to more parallel executed threads. As Fig. 4(b) shows, the performance of CPR scheme is in inverse ratio to the density of data sharing among nesting levels. The higher the density is, the fewer the partial rollback occurs for the CPR scheme, and the speedup over flattening model is more approximate to 1; in contrast, with the density of data sharing Transactions Started / Committed 121 101 81 61 41 21 flattening CPR 1 2 4 8 16 Number of Processors (a) CPR vs. flattening for different processornumbers Transactions Started / Committed 121 101 81 61 41 21 1 flattening CPR 1 2 3 4 Number of Nesting-levels (b) CPR vs. flattening for different nesting levels Fig. 5. Ratio of started transactions to committed transactions
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Lecture Notes in Computer Science 5
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Volume Editors Christian Müller-Sc
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General Chair Organization Christia
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Organization IX Hartmut Schmeck Kar
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Keynote Table of Contents HyVM - Hy
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Table of Contents XIII JetBench:AnO
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How to Enhance a Superscalar Proces
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4 J. Mische et al. The Real-time Vi
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6 J. Mische et al. 4.1 Instruction
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8 J. Mische et al. Additionally the
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10 J. Mische et al. % of unused pip
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12 J. Mische et al. % of cycles spe
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14 J. Mische et al. 16. Lickly, B.,
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16 G. Aşılıoğlu, E.M. Kaya, and
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26 T.B. Preußer, P. Reichel, and R
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38 P. Bellasi, W. Fornaciari, and D
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50 J. Zeppenfeld and A. Herkersdorf
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62 B. Jakimovski, B. Meyer, and E.
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74 M. Bonn and H. Schmeck Fig. 1. J
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76 M. Bonn and H. Schmeck 2.2 Node
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78 M. Bonn and H. Schmeck Uptime-ba
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80 M. Bonn and H. Schmeck 2.4 Simul
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82 M. Bonn and H. Schmeck done rate
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84 M. Bonn and H. Schmeck Fig. 8. J
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86 M. Bonn and H. Schmeck tells the
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88 J.-P. Steghöfer et al. � �
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90 J.-P. Steghöfer et al. mechanis
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92 J.-P. Steghöfer et al. resource
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94 J.-P. Steghöfer et al. Choose a
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196 M. Schindewolf, D. Kramer, and
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198 M. Schindewolf, D. Kramer, and
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200 R. Plyaskin and A. Herkersdorf
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212 M.Y. Qadri, D. Matichard, and K
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A Tightly Coupled Accelerator Infra
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224 F. Nowak and R. Buchty where A
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226 F. Nowak and R. Buchty Fig. 3.
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228 F. Nowak and R. Buchty Table 2.
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230 F. Nowak and R. Buchty Table 4.
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232 F. Nowak and R. Buchty 5.3 Comp
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Optimizing Stencil Application on M
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236 F. Xudong et al. compared to th
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238 F. Xudong et al. stencil comput
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240 F. Xudong et al. threads in the
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242 F. Xudong et al. Speedup 14 12
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244 F. Xudong et al. 5 Related Work
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Abdullah, Tariq 174 Alima, Luc Onan
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