TECHNOLOGIES FOR INDIRECTLY CALLING VECTOR FUNCTIONS
    1.
    发明申请
    TECHNOLOGIES FOR INDIRECTLY CALLING VECTOR FUNCTIONS 审中-公开
    间接呼叫矢量功能的技术

    公开(公告)号:WO2017153796A1

    公开(公告)日:2017-09-14

    申请号:PCT/IB2016/000404

    申请日:2016-03-11

    Abstract: Technologies for indirectly calling vector functions include a compute device that includes a memory device to store source code and a compiler module. The compiler module is to identify a set of declarations of vector variants for scalar functions in the source code, generate a vector variant address map for each set of vector variants, generate an offset map for each scalar function, and identify, in the source code, an indirect call to the scalar functions, wherein the indirect call is to be vectorized. The compiler module is also to determine, based on a context of the indirect call, a vector variant to be called and store, in object code and in association with the indirect call, an offset into one of the vector variant address maps based on (i) the determined vector variant to be called and (ii) the offset map that corresponds to each scalar function.

    Abstract translation: 用于间接调用向量函数的技术包括包含存储源代码的存储器设备和编译器模块的计算设备。 编译器模块将为源代码中的标量函数标识矢量变体的一组声明,为每组矢量变体生成矢量变体地址映射,为每个标量函数生成偏移映射,并在源代码中标识 ,间接调用标量函数,其中间接调用将被矢量化。 编译器模块还基于间接调用的上下文来确定待调用的矢量变体,并且以目标代码并且与间接调用相关联地将偏移量存储到矢量变体地址映射之一中,基于( i)确定的要调用的矢量变体和(ii)与每个标量函数相对应的偏移映射。

    GENERATING VECTOR BASED SELECTION CONTROL STATEMENTS

    公开(公告)号:WO2018125409A1

    公开(公告)日:2018-07-05

    申请号:PCT/US2017/061713

    申请日:2017-11-15

    CPC classification number: G06F9/3844 G06F9/30058 G06F9/3806 G06F15/76

    Abstract: In one example, a system for generating vector based selection control statements can include a processor to determine a vector cost of the selection control statement is below a scalar cost and determine the selection control statement is to be executed in a sorted order based on dependencies between branch instructions of the selection control statement. The processor can also determine a program ordering of labels of the selection control statement does not match a mathematical ordering of the labels and execute the selection control statement with a vector of values, wherein the selection control statement is to be executed based on a jump table and a sorted unique value technique, wherein the sorted unique value technique comprises selecting at least one of the plurality of branch instructions from the jump table.

    METHODS AND APPARATUSES FOR THREAD MANAGEMENT OF MULTI-THREADING
    6.
    发明申请
    METHODS AND APPARATUSES FOR THREAD MANAGEMENT OF MULTI-THREADING 审中-公开
    多线程螺纹管理的方法和设备

    公开(公告)号:WO2005033936A1

    公开(公告)日:2005-04-14

    申请号:PCT/US2004/032075

    申请日:2004-09-29

    CPC classification number: G06F8/441

    Abstract: Methods and apparatuses for thread management for multi-threading are described herein. In one embodiment, exemplary process includes selecting, during a compilation of code having one or more threads executable in a data processing system, a current thread having a most bottom order, determining resources allocated to one or more child threads spawned from the current thread, and allocating resources for the current thread in consideration of the resources allocated to the current thread's one or more child threads to avoid resource conflicts between the current thread and its one or more child threads. Other methods and apparatuses are also described.

    Abstract translation: 本文描述了用于多线程的线程管理的方法和装置。 在一个实施例中,示例性过程包括在具有在数据处理系统中可执行的一个或多个线程的代码的编译期间选择具有最低阶的当前线程,确定分配给从当前线程产生的一个或多个子线程的资源, 并且考虑分配给当前线程的一个或多个子线程的资源来为当前线程分配资源,以避免当前线程与其一个或多个子线程之间的资源冲突。 还描述了其它方法和装置。

    THREAD-DATA AFFINITY OPTIMIZATION USING COMPILER
    7.
    发明申请
    THREAD-DATA AFFINITY OPTIMIZATION USING COMPILER 审中-公开
    使用编译器的线程优化优化

    公开(公告)号:WO2007041122A1

    公开(公告)日:2007-04-12

    申请号:PCT/US2006/037576

    申请日:2006-08-26

    CPC classification number: G06F8/45

    Abstract: Thread-data affinity optimization can be performed by a compiler during the compiling of a computer program to be executed on a cache coherent non-uniform memory access (cc-NUMA) platform. In one embodiment, the present invention includes receiving a program to be compiled. The received program is then compiled in a first pass and executed. During execution, the compiler collects profiling data using a profiling tool. Then, in a second pass, the compiler performs thread-data affinity optimization on the program using the collected profiling data.

    Abstract translation: 线程数据亲和度优化可以在编译要在高速缓存相干非均匀内存访问(cc-NUMA)平台上执行的计算机程序时由编译器执行。 在一个实施例中,本发明包括接收要编译的程序。 接收的程序然后被编译成第一遍并被执行。 在执行期间,编译器使用分析工具收集分析数据。 然后,在第二遍,编译器使用收集的分析数据对程序执行线程数据关联优化。

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