会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 3. 发明授权
    • Systems and methods for tracking working-set estimates with a limited resource budget
    • 以有限的资源预算跟踪工作集估计的系统和方法
    • US08769202B1
    • 2014-07-01
    • US13198495
    • 2011-08-04
    • Gokul SoundararajanLakshmi Narayanan BairavasundaramVipul MathurKaladhar Voruganti
    • Gokul SoundararajanLakshmi Narayanan BairavasundaramVipul MathurKaladhar Voruganti
    • G06F12/00
    • G06F12/0802G06F12/0888G06F2212/6042
    • Embodiments of the systems and techniques described here can leverage several insights into the nature of workload access patterns and the working-set behavior to reduce the memory overheads. As a result, various embodiments make it feasible to maintain running estimates of a workload's cacheability in current storage systems with limited resources. For example, some embodiments provide for a method comprising estimating cacheability of a workload based on a first working-set size estimate generated from the workload over a first monitoring interval. Then, based on the cacheability of the workload, a workload cache size can be determined. A cache then can be dynamically allocated (e.g., change, possibly frequently, the cache allocation for the workload when the current allocation and the desired workload cache size differ), within a storage system for example, in accordance with the workload cache size.
    • 这里描述的系统和技术的实施例可以利用对工作负载访问模式和工作集行为的性质的几个见解,以减少内存开销。 因此,各种实施例使得可以在有限的资源的当前存储系统中维持工作负载的高速缓存的运行估计。 例如,一些实施例提供了一种方法,其包括基于在第一监视间隔上从工作负载产生的第一工作集大小估计来估计工作负载的可缓存性。 然后,基于工作负载的可缓存性,可以确定工作负载高速缓存大小。 然后可以根据工作负载高速缓存大小来动态地分配高速缓存(例如,当当前分配和期望的工作负载高速缓存大小不同时,可以频繁地改变工作负载的高速缓存分配),例如在存储系统内。
    • 9. 发明授权
    • Optimizing distributed data analytics for shared storage
    • 优化共享存储的分布式数据分析
    • US09122535B2
    • 2015-09-01
    • US13302306
    • 2011-11-22
    • Gokul SoundararajanMadalin Mihailescu
    • Gokul SoundararajanMadalin Mihailescu
    • G06F9/46G06F9/50
    • H04L67/2842G06F9/5066G06F12/0815G06F12/0862G06F12/0868G06F17/30132G06F17/30194G06F2212/284H04L67/06
    • Methods, systems, and computer executable instructions for performing distributed data analytics are provided. In one exemplary embodiment, a method of performing a distributed data analytics job includes collecting application-specific information in a processing node assigned to perform a task to identify data necessary to perform the task. The method also includes requesting a chunk of the necessary data from a storage server based on location information indicating one or more locations of the data chunk and prioritizing the request relative to other data requests associated with the job. The method also includes receiving the data chunk from the storage server in response to the request and storing the data chunk in a memory cache of the processing node which uses a same file system as the storage server.
    • 提供了用于执行分布式数据分析的方法,系统和计算机可执行指令。 在一个示例性实施例中,执行分布式数据分析作业的方法包括在分配用于执行任务以识别执行任务所需的数据的处理节点中收集特定于应用的信息。 该方法还包括基于指示数据块的一个或多个位置的位置信息和相对于与该作业相关联的其它数据请求对该请求进行优先级排序从存储服务器请求一组必要数据。 该方法还包括响应于请求从存储服务器接收数据块,并将数据块存储在使用与存储服务器相同的文件系统的处理节点的存储器高速缓存中。