While optimizing a matrix manipulation code in C, I used CilkPlus to spawn a thread to execute in parallel two functions that are data independent and somewhat computationally intensive. Cilk_spawn is used in only one place in the code as follows:
I would like to understand run-time execution in Cilk a little better.
I have downloaded Intel Cilk run-time release (cilkplus-rtl-003365 - released 3-May-2013).
On 09/09/2013 I had asked a question seeking to figure out which is the last function executed before Cilk run-time ends assuming execution went without any problems.
Barry suggested to look at “__cilkrts_c_return_from_initial()” in scheduler.c and indeed that was what I needed at that time.
I was wondering whether there was some way to modify the makefiles for the GCC build of Cilk Plus to keep the labels for debugging (i.e. compile with -g). I am trying to get a fuller picture of how the runtime system works in order to possibly modify it
I would like to understand Cilk worker creation a litter better.
I am not sure how to phrase this question so I’ll give it my best.
I have downloaded Intel Cilk runtime release (cilkplus-rtl-003365 - released 3-May-2013).
I would like to create a new Cilk worker that does not cause cross-threading issues but this new worker would not be a part of the work collective.
I noticed in the Intel Cilk Plus runtime library change log (https://www.cilkplus.org/sites/default/files/runtime_source/changes-3453...), support for ARM with Intel C/C++ Compiler mainline-to-14.0 branch cutoff. Is there any possibility to use the beautiful cilk plus on the ARM architecture?
Is std::vector support concurrently read - write access for Cilk workers ? And which vector operator should I use ? Now I'm using like " data [i] = x ; " for assignment.
P1 and P2 data race problems are appear when I inspect program . I haven`t got experience about Cilk Plus. I guess error is occur in nested loop . What should I do ?
作者： 英特尔高级软件应用工程师 Zvi Danovich
大部分的 Android 应用 — 即使是仅基于脚本和管理语言 (Java*, HTML5,…) 的应用 — 最终都会使用中间件功能，因为该功能能够利用优化特性。
本文将介绍基于 Android 的优化需求和方法，并详述一个优化多媒体和增强现实应用的案例。
英特尔为 Android 平台（智能手机和平板电脑）提供了多种不同的英特尔® 凌动™ 处理器，至少包括英特尔® SIMD 流指令扩展补充版（英特尔® SSSE3）级别的矢量功能，通常包括两个内核和超线程。