公开(公告)号：US20170024191A1

公开(公告)日：2017-01-26

申请号：US14803110

申请日：2015-07-20

Applicant: QUALCOMM INCORPORATED

Inventor： JAMES LYALL ESLIGER ,  WILSON KWAN ,  MARK BAPST

IPC: G06F9/45 ,  G06F9/44

CPC classification number: G06F8/41 ,  G06F1/324 ,  G06F1/329 ,  G06F1/3296 ,  G06F8/443 ,  G06F8/71 ,  G06F9/50 ,  G06F11/3409 ,  G06F11/3442 ,  Y02D10/22

Abstract: Various embodiments of methods and systems for proactive resource allocation and configuration are disclosed. An exemplary method first compiles and links a profile instrumented application with a compiler comprising a profile guided optimization feature that inserts calls to a profiler runtime. The profile instrumented application is executed on a target device using one or more workload datasets representative of probable workloads. During execution, based on recognition of the inserted calls, an instrumentation-based profile dataset is generated in association with each of the one or more workload datasets. Next, the profile instrumented application is recompiled and relinked based on the instrumentation-based profile datasets to create a set of profile guided optimizations to the source code, thereby resulting in an optimized application. The optimized application may be executed and monitored to generate a revised profile dataset useful for providing instructions to the target device for optimal workload allocation and resource configuration.

Abstract translation: 公开了用于主动资源分配和配置的方法和系统的各种实施例。 一种示例性方法首先将配置文件测试的应用程序与编译器进行编译并链接，该编译器包括将调用插入到轮廓仪运行时的轮廓引导优化特征。 使用一个或多个表示可能工作负载的工作负载数据集，在目标设备上执行配置文件化应用程序。 在执行期间，基于对插入的呼叫的识别，与一个或多个工作负载数据集中的每一个相关联地生成基于仪表的配置文件数据集。 接下来，基于基于仪器的配置文件数据集重新编译和重新链接配置文件的应用程序，以创建一组对源代码进行的轮廓引导优化，从而导致优化的应用程序。 可以执行和监视优化的应用程序以生成修改的简档数据集，其用于向目标设备提供用于最佳工作负载分配和资源配置的指令。

公开(公告)号：US20160335127A1

公开(公告)日：2016-11-17

申请号：US14709385

申请日：2015-05-11

Applicant: QUALCOMM INCORPORATED

Inventor： JAMES MICHAEL ARTMEIER ,  SUMIT SUR ,  ROBERT SCOTT DREYER ,  MICHAEL DOUGLAS SHARP ,  JAMES LYALL ESLIGER

IPC: G06F9/50

CPC classification number: G06F9/5044 ,  G06F9/505 ,  G06F9/5066 ,  G06F9/5083 ,  Y02D10/22 ,  Y02D10/36

Abstract: Systems and methods for dynamic granularity control of parallelized work in a heterogeneous multi-processor portable computing device (PCD) are provided. During operation a first parallelized portion of an application executing on the PCD is identified. The first parallelized portion comprising a plurality of threads for parallel execution on the PCD. Performance information is obtained about a plurality of processors of the PCD, each of the plurality of processors corresponding to one of the plurality of threads. A number M of workload partition granularities for the plurality of threads is determined, and a total execution cost for each of the M workload partition granularities is determined An optimal granularity comprising a one of the M workload partition granularities with a lowest total execution cost is determined, and the first parallelized portion is partitioned into a plurality of workloads having the optimal granularity.

Abstract translation: 提供了一种用于异构多​​处理器便携式计算设备（PCD）中并行工作的动态粒度控制的系统和方法。 在操作期间，识别在PCD上执行的应用程序的第一并行化部分。 第一并行部分包括用于在PCD上并行执行的多个线程。 获得关于PCD的多个处理器的性能信息，所述多个处理器中的每一个对应于所述多个线程之一。 确定多个线程的M个工作负载分区粒度，并且确定每个M个工作负载分区粒度的总执行成本确定包括具有最低总执行成本的M个工作负载分区粒度之一的最佳粒度 并且第一并行化部分被划分为具有最佳粒度的多个工作负载。