187 research outputs found
Modeling human-caused forest fire ignition for assessing forest fire danger in Austria
Prognostic impact of progression to induction chemotherapy and prior paclitaxel therapy in patients with germ cell tumors receiving salvage high-dose chemotherapy in the last 10 years: A study of the European Society for Blood and Marrow Transplantation Solid Tumors Working Party
Little is known about the prognostic impact of prior paclitaxel therapy and response to induction chemotherapy defined as the regimen preceding high-dose chemotherapy (HDCT) for the salvage therapy of advanced germ cell tumors. Twenty European Society for Blood and Marrow Transplantation centers contributed data on patients treated between 2002 and 2012. Paclitaxel used in either prior lines of therapy or in induction-mobilization regimens was considered. Multivariable Cox analyses of prespecified factors were undertaken on PFS and overall survival (OS). As of October 2013, data for 324 patients had been contributed to this study. One hundred and ninety-two patients (59.3%) had received paclitaxel. Sixty-one patients (19%) had a progression to induction chemotherapy, 234 (72%) a response (29 (9%) missing or granulocyte colony-stimulating factor without chemotherapy). Both progression to induction chemotherapy and prior paclitaxel were significantly associated with shorter OS univariably (P<0.001 and P=0.032). On multivariable analysis from the model with fully available data (N=216) progression to induction was significantly prognostic for PFS and OS (P=0.003), but prior paclitaxel was not (P=0.674 and P=0.739). These results were confirmed after multiple imputation of missing data. Progression to induction chemotherapy could be demonstrated as an independent prognostic factor, in contrast to prior paclitaxel
The architectural costs of streaming I/O: A comparison of workstations, clusters, and SMPs
We investigate resource usage while performing streaming I/O by contrasting three architectures, a single workstation, a cluster, and an SMP, under various I/O benchmarks. We derive analytical and empirically-1Introduction based models of resource usage during data transfer, examining the I/O bus, memory bus, network, and processor of each system. By investigating each resource in detail, we assess what comprises a wellbalanced system for these workloads. We find that the architectures we study are not well balanced for streaming I/O applications. Across the platforms, the main limitation to attaining peak performance is the CPU, due to lack of data locality. Increasing processorperformance (especially with improved block operation performance) will be of great aid for these workloads in the future. For a cluster workstation, the I/O bus is a major system bottleneck, because of the increased load placed on it from network communication. A well-balanced cluster workstation should have copious I/O bus bandwidth, perhaps via multiple I/O busses. The SMP suffers from poor memory-system performance; even when there is true parallelism in the benchmark, contention in the shared-memory system leads to reduced performance. As a result, the clustered workstations provide higher absolute performance for streaming I/O workloads
High-Performance Sorting on Networks of Workstations
We report the performance of NOW-Sort, a collection of sorting implementations on a Network of Workstations (NOW). We find that paraflel sorting on a NOW is competitive to sorting on the large-scale SMPS that have traditionally held the performance records. On a 64-node cluster, we sort 6.0 GB in just under one minute, while a 32-node cluster finishes the Datamation benchmark in 2.41 seconds. Our implementations can be applied to a variety of disk, memory, and processor configurations; we highlight salient issues for tuning each component of the system. We evaluate the use of commodity operating systems and hardware for parallel sorting. We find existing OS primitives for memory management and file access adequate. Due to aggregate communication and disk bandwidth requirements, the bottleneck of our system is the workstation I/O bus
High-performance sorting on networks of workstations
Pierre-Amiel Giraud a créé une page sur laquelle se trouve une liste de plugins de recherche pour la plate-forme Isidore. Il y a un plugin par collection moissonnée, et la liste est automatiquement mise à jour chaque lundi. Il suffit de cliquer sur le bouton correspondant à la collection qui vous intéresse pour installer le plugin ! http://www.insolit.org/2013/06/plugins-de-recherche-pour-la-plate-forme-isidore/  Pour la collection LIRE et la source Bouvard, c'est sur cette page : http://www...
High-Performance Sorting on Networks of Workstations
We report the performance of NOW-Sort, a collection of sorting implementations on a Network of Workstations (NOW). We find that parallel sorting on a NOW is competitive to sorting on the large-scale SMPs that have traditionally held the performance records. On a 64-node cluster, we sort 6.0 GB in just under one minute, while a 32-node cluster finishes the Datamation benchmark in 2.41 seconds. Our implementations can be applied to a variety of disk, memory, and processor configurations; we highlight salient issues for tuning each component of the system. We evaluate the use of commodity operating systems and hardware for parallel sorting. We find existing OS primitives for memory management and file access adequate. Due to aggregate communication and disk bandwidth requirements, the bottleneck of our system is the workstation I/O bus
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