Abstract: The present invention discloses a extra thick hot rolled H section steel and a production method therefor. The extra thick hot rolled H section steel contains, by mass, the following chemical components: 0.04-0.11% of C, 0.10-0.40% of Si, 0.40-1.00% of Mn, 0.40-1.00% of Cr, 0.10-0.40% of Cu, 0.020-0.060% of Nb, 0.040-0.100% of V, 0.010-0.025% of Ti, 0.010-0.030% of Al, 0.0060-0.0120% of N, not more than 0.015% of P, not more than 0.005% of S, not more than 0.0060% of O, and the balance Fe and trace residual elements, wherein 0.090%?Nb+V+Ti?0.170%, 6.5?(V+Ti)/N?10.5, and 0.30%?CEV?0.48%. The extra thick hot rolled H section steel has a flange thickness of 90 mm-150 mm, has excellent comprehensive mechanical properties, and can well meet the needs for heavy supporting structural parts of high-rise buildings, large squares, bridge structures, etc.

Abstract: A scheduler obtains a to-be-processed job; and controls at least one super node based on a resource requirement of the to-be-processed job to process the to-be-processed job based on a global memory pool of the super node, where the to-be-processed job is a processing request related to a distributed application. In this way, because the global memory pool is a resource that is constructed through unified addressing on storage media of nodes in the super node and that is shared by the nodes in the super node, the nodes in the super node that are coupled using a high-speed interconnection technology share and access the global memory pool to process the to-be-processed job.

Abstract: A method includes: receiving a fast Fourier transformation FFT execution request sent by an application program; obtaining first input data on which an FFT calculation needs to be performed; decomposing the FFT calculation into a plurality of calculation stages based on a cardinality of the FFT calculation, where each calculation stage includes a DFT calculation; determining a DFT calculation matrix corresponding to the DFT calculation in each calculation stage; determining, based on input data of a corresponding calculation stage when a calculation of each calculation stage is performed, a first data matrix on which a matrix operation is performed with the DFT calculation matrix; and performing a matrix multiplication calculation on the DFT calculation matrix and the first data matrix to implement the DFT calculation, and returning a calculation result to the application program after the plurality of calculation stages are completed.

Abstract: The present invention discloses a extra thick hot rolled H section steel and a production method therefor. The extra thick hot rolled H section steel contains, by mass, the following chemical components: 0.04-0.11% of C, 0.10-0.40% of Si, 0.40-1.00% of Mn, 0.40-1.00% of Cr, 0.10-0.40% of Cu, 0.020-0.060% of Nb, 0.040-0.100% of V, 0.010-0.025% of Ti, 0.010-0.030% of Al, 0.0060-0.0120% of N, not more than 0.015% of P, not more than 0.005% of S, not more than 0.0060% of O, and the balance Fe and trace residual elements, wherein 0.090%?Nb+V+Ti?0.170%, 6.5?(V+Ti)/N?10.5, and 0.30%?CEV?0.48%. The extra thick hot rolled H section steel has a flange thickness of 90 mm-150 mm, has excellent comprehensive mechanical properties, and can well meet the needs for heavy supporting structural parts of high-rise buildings, large squares, bridge structures, etc.

Abstract: The present disclosure relates to methods and apparatuses for processing a control packet in a collective communication system, where the collective communication system includes a switch network and multiple computing nodes, and the switch network includes a first switch. In one example method, the first switch forwards a query packet transmitted by a source node to a destination node, where the query packet is generated by the source node based on a context of the collective communication system. Then, the first switch forwards a notification packet transmitted by the destination node to the source node, where the notification packet carries an in-network computing capability of the switch network.

Abstract: A computer-implemented method, a computer system and a computer program product for releasable resource-based preemptive scheduling. One or more currently running workloads are determined to be preempted by a pending workload. Releasable resources from the one or more currently running workloads meet required resources of the pending workload. The pending workload is dispatched so that it uses at least part of the releasable resources from the one or more currently running workloads to run.

Abstract: A method and system for process tracking is disclosed. A first process is associated with an identity of a job, wherein the first process is launched by an outsourcing process to process the job. A second process is created locally. The second process is associated with the identity of the job to enable the second process to manage the first process based on the identity.

Abstract: A computer-implemented method, a computer system and a computer program product for releasable resource-based preemptive scheduling. One or more currently running workloads are determined to be preempted by a pending workload. Releasable resources from the one or more currently running workloads meet required resources of the pending workload. The pending workload is dispatched so that it uses at least part of the releasable resources from the one or more currently running workloads to run.

Abstract: A method and system for process tracking is disclosed. A first process is associated with an identity of a job, wherein the first process is launched by an outsourcing process to process the job. A second process is created locally. The second process is associated with the identity of the job to enable the second process to manage the first process based on the identity.

Abstract: A technique for allocating a global resource in a distributed grid environment includes receiving from slave resource managers use and demand data associated with the global resource by each consumer in a respective region. A master resource manager computes an allocation of the global resource for each consumer and for each region based on the use data and the demand data. The master resource manager then communicates to each slave resource manager an amount of the global resource allocated to each consumer in each respective region controlled by a respective slave resource manager and a total allocation of the global resource for the region controlled by the respective slave resource manager.

Abstract: A technique for allocating a global resource in a distributed grid environment includes a master resource manager (MRM), and a plurality of slave resource managers (SRMs) each configured to allocate a global resource within a respectively controlled region of a distributed grid computing environment. The MRM receives from each SRM use data and demand data associated with the global resource by each consumer in the respective region controlled by the respective SRM. The MRM then computes an allocation of the global resource for each consumer and for each region based on the use data and the demand data. The MRM then communicates to each SRM an amount of the global resource allocated to each consumer in each respective region controlled by a respective SRM and a total allocation of the global resource for the region controlled by the respective SRM.

Abstract: A computer-implemented method comprises identifying a computer task; determining a hardware exception source associated with the computer task; determining an exception unit associated with the hardware exception source; determining a parallelization factor associated with the hardware exception source; and determining a parallel execution scenario associated with the computer task based on the exception unit and the parallelization factor. A corresponding computer program product and computer system are also disclosed.

Abstract: A method for estimating job start times on a system may include: performing a first simulation of the system by a first process to generate a first estimate of the start time based a first snapshot of the computing system; and performing a second simulation of the system to generate a second estimate of the start time. The first and second estimates may each be either a distinct time estimate or a range of time estimate, depending on whether the simulations dispatches the job before the respective first and second processes end. The method may then include generating a fifth estimate of the time that the computing job will start by a third process based on estimates respectively generated by the first and second processes.

Abstract: A computer-implemented method comprises identifying a computer task; determining a hardware exception source associated with the computer task; determining an exception unit associated with the hardware exception source; determining a parallelization factor associated with the hardware exception source; and determining a parallel execution scenario associated with the computer task based on the exception unit and the parallelization factor. A corresponding computer program product and computer system are also disclosed.

Abstract: A computer-implemented method comprises identifying a computer task; determining a hardware exception source associated with the computer task; determining an exception unit associated with the hardware exception source; determining a parallelization factor associated with the hardware exception source; and determining a parallel execution scenario associated with the computer task based on the exception unit and the parallelization factor. A corresponding computer program product and computer system are also disclosed.

Abstract: A method for estimating job start times on a system may include: performing a first simulation of the system by a first process to generate a first estimate of the start time based a first snapshot of the computing system; and performing a second simulation of the system to generate a second estimate of the start time. The first and second estimates may each be either a distinct time estimate or a range of time estimate, depending on whether the simulations dispatches the job before the respective first and second processes end. The method may then include generating a fifth estimate of the time that the computing job will start by a third process based on estimates respectively generated by the first and second processes.

Abstract: A method for estimating job start times on a system may include: performing a first simulation of the system by a first process to generate a first estimate of the start time based a first snapshot of the computing system; and performing a second simulation of the system to generate a second estimate of the start time. The first and second estimates may each be either a distinct time estimate or a range of time estimate, depending on whether the simulations dispatches the job before the respective first and second processes end. The method may then include generating a fifth estimate of the time that the computing job will start by a third process based on estimates respectively generated by the first and second processes.

Abstract: A technique for allocating a global resource in a distributed grid environment includes a master resource manager (MRM), and a plurality of slave resource managers (SRMs) each configured to allocate a global resource within a respectively controlled region of a distributed grid computing environment. The MRM receives from each SRM use data and demand data associated with the global resource by each consumer in the respective region controlled by the respective SRM. The MRM then computes an allocation of the global resource for each consumer and for each region based on the use data and the demand data. The MRM then communicates to each SRM an amount of the global resource allocated to each consumer in each respective region controlled by a respective SRM and a total allocation of the global resource for the region controlled by the respective SRM.

Abstract: A technique for allocating a global resource in a distributed grid environment includes receiving from slave resource managers use and demand data associated with the global resource by each consumer in a respective region. A master resource manager computes an allocation of the global resource for each consumer and for each region based on the use data and the demand data. The master resource manager then communicates to each slave resource manager an amount of the global resource allocated to each consumer in each respective region controlled by a respective slave resource manager and a total allocation of the global resource for the region controlled by the respective slave resource manager.

Abstract: A technique for allocating a global resource in a distributed grid environment includes: a master resource manager (MRM) that receives from slave resource managers use and demand data associated with a global resource by each consumer in a region controlled by a respective slave resource manager. The MRM computes an allocation of the resource for each consumer and for each region by determining a total amount of the resource to allocate, estimating a need by each consumer for the resource based on the use and demand data, determining an allocation of the total amount of the resource among the consumers based on the estimated need; subdividing the allocation for each consumer among each region where the consumer utilizes the resource; and computing a total allocation of the resource for each region.