100 research outputs found
ΠΡΠΎΡΠ΅ΡΡΠΎΡΡ Π. Π. ΠΠΎΡΠΈΠΊΠΎΠ²Ρ - 70 Π»Π΅Ρ
1 ΡΠ½Π²Π°ΡΡ 2012 Π³. ΠΎΡΠΌΠ΅ΡΠΈΠ» ΡΠ±ΠΈΠ»Π΅ΠΉ Π΄ΠΎΠΊΡΠΎΡ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
Π½Π°ΡΠΊ, ΠΏΡΠΎΡΠ΅ΡΡΠΎΡ, ΠΠ°ΡΠ»ΡΠΆΠ΅Π½Π½ΡΠΉ Π΄Π΅ΡΡΠ΅Π»Ρ Π½Π°ΡΠΊΠΈ Π Π€, ΠΠΎΡΠ΅ΡΠ½ΡΠΉ ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊ Π²ΡΡΡΠ΅Π³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ Π Π€ ΠΈ ΠΠΎΡΠ΅ΡΠ½ΡΠΉ ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊ Π½Π°ΡΠΊΠΈ ΠΈ ΡΠ΅Ρ
Π½ΠΈΠΊΠΈ Π Π€ ΠΠ½Π°ΡΠΎΠ»ΠΈΠΉ ΠΠΈΡ
Π°ΠΉΠ»ΠΎΠ²ΠΈΡ ΠΠΎΡΠΈΠΊΠΎΠ²
Π Π½Π΅ΠΊΠΎΡΠΎΡΡΡ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡΡ Π΄Π°Π»ΡΠ½Π΅ΠΉΡΠ΅ΠΉ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΠΈ Π±Π΅ΡΠ°ΡΡΠΎΠ½ΠΎΠ²
The novel ScaleMP vSMP architecture employs commodity x86-based servers with an InfiniBand network to assemble a large shared memory system at an attractive price point. We examine this combined hardware- and softwareapproach of a DSM system using both system-level kernel benchmarks as well as real-world application codes. We compare this architecture with traditional shared memory machines and elaborate on strategies to tune application codes parallelized with OpenMP on multiple levels. Finally we summarize the necessary conditions which a scalable application has to fulfill in order to profit from the full potential of the ScaleMP approach
COMMON MARKETING MISTAKES
An efficient parallel algorithm for the computation of parametric sensitivities for differential-algebraic equations (DAEs) with a focus on dynamic optimization problems is presented. A speedup of about 4 can be obtained for process models of more than 13500 DAEs and 75 parameters employing 8 processor cores in parallel using a Windows based system. The algorithm obtains its efficiency by decoupling the sensitivity equations from the state equations of the DAE. Furthermore, the costly Jacobian matrices are computed separately by other processes. The computational effort for a combined state and sensitivity integration can almost be reduced to the computational effort of the pure state integration, which is the theoretical limit of the suggested approach
Π ΡΠ΅ΠΆΠΈΠΌΠ΅ ΠΊΡΠ°ΡΠΊΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ ΠΎΡΠΏΡΡΠΊΠΎΠ² Π±ΡΡΡΡΠΎΡΠ΅ΠΆΡΡΠ΅ΠΉ ΡΡΠ°Π»ΠΈ
H2M: Towards Heuristics for Heterogeneous Memory
International audienc
- β¦