Cilk Home Page | CilkPlus
Why Use it? Intel© Cilk™ Plus is the easiest, quickest way to harness the power of both multicore and vector processing. What is it? Intel Cilk Plus is an extension to the C and C++ languages to support data and task parallelism.
Phoronix: A Linux Compiler Deathmatch: GCC, LLVM, DragonEgg, Open64, Etc…
Open64 had an incredibly strong finish when looking at the performance of its resulting C-Ray binary. Open64’s C-Ray binary was over 40% faster than the GCC and LLVM-GCC / DragonEgg releases tested. Open64 was also produced a blazing fast binary for Himeno that was 93% faster than the second fastest compiler, LLVM-GCC 4.2.1, and 2.6 times faster than GCC 4.5.1.
ccache is a compiler cache. It speeds up recompilation by caching previous compilations and detecting when the same compilation is being done again. Supported languages are C, C++, Objective-C and Objective-C++.
Re: [ccache] Stumbling blocks with ccache and embedded/encapsulated environments
if your ‘make’ dependencies or equivalent are well-written, using ccache will almost always *increase* your incremental build times. This wasn’t immediately obvious to us but makes sense in hindsight: if your dependencies are well constructed, then when you run ‘make’ it won’t try to build something unless it really has changed. We see *very* few ccache hits over time when doing incremental builds. Slightly longer version: if your ‘make’ dependencies are well-written, then using ccache will almost always increase your incremental build times. Even if your dependencies are slightly inefficient (i.e. you’re getting some unnecessary compilation on a regular basis, but not tons), ccache may well still be slowing you down overall on incremental builds unless your computers have lots of RAM relative to the size of your project. It turns out that fitting the build inputs *and* outputs into the VM/filesystem buffer cache usually provides much more build-time benefit than ccache. (Unless
developer.nvidia.com: CUDACasts Episode #6: CUDA on ARM with CUDA 5.5
In CUDACast #5, we saw how to use the new NVIDIA RPM and Debian packages to install the CUDA toolkit, samples, and driver on a supported Linux OS with a standard package manager. With CUDA 5.5, it is now possible to compile and run CUDA applications on ARM-based systems such as the Kayla development platform.