thread-local-storage

I use Go and Gin to setup my website and want to know the database access time. I use goroutine so if don't use something like thread-local, I must change almost every function to do it. Does Go have a good way to do it? The Go runtime and standard libraries do not provide goroutine local storage or a goroutine identifier that can be used to implement goroutine local storage. The third party gls package implements goroutine local storage in an interesting way. Some find this package horrifying and others think it's clever. The Go team recommends passing context explicitly as function argument

Now that C++ is adding thread_local storage as a language feature, I'm wondering a few things: What is the cost of thead_local likely to be? In memory? For read and write operations? Associated with that: how do Operating Systems usually implement this? It would seem like anything declared thread_local would have to be given thread-specific storage space for each thread created. Storage space: size of the variable * number of threads, or possibly (sizeof(var) + sizeof(var*)) * number of threads. There are two basic ways of implementing thread-local storage: Using some sort of system call that

Do Java ThreadLocal variables produce thread-local values if they are used as instance variables (e.g., in a method that generates thread-local objects), or must they always be static to do so? As an example, assume a typical scenario where several, expensive to initialize objects of a class that is not thread-safe, need to be instantiated in a single static initialization block, stored in static variables of a single class (e.g., in a Map data structure) and from then on used for intensive processing by numerous different threads. To achieve thread safety, obviously a different copy of each

I'm trying to use Cython to parallelize an expensive operation which involves generating intermediate multidimensional arrays. The following very simplified code illustrates the sort of thing I'm trying to do: import numpy as np cimport cython cimport numpy as np from cython.parallel cimport prange from libc.stdlib cimport malloc, free @cython.boundscheck(False) @cython.wraparound(False) def embarrasingly_parallel_example(char[:, :] A): cdef unsigned int m = A.shape[0] cdef unsigned int n = A.shape[1] cdef np.ndarray[np.float64_t, ndim = 2] out = np.empty((m, m), np.float64) cdef unsigned int

I'm working on a custom mark-release style memory allocator for the D programming language that works by allocating from thread-local regions. It seems that the thread local storage bottleneck is causing a huge (~50%) slowdown in allocating memory from these regions compared to an otherwise identical single threaded version of the code, even after designing my code to have only one TLS lookup per allocation/deallocation. This is based on allocating/freeing memory a large number of times in a loop, and I'm trying to figure out if it's an artifact of my benchmarking method. My understanding is

I am trying to use __thread in this small program without luck. Any idea if this TLS is supported in ndk 10c clang 3.4/3.5? The same program compiles fine with ndk gcc 4.8/4.9 and native clang/gcc compilers. Here is the program and compile line - __thread int counter; int main () { counter=20; return 0; } [armeabi] Compile++ thumb: test <= test.cpp /Users/padlar/android/android-ndk-r10c/toolchains/llvm-3.5/prebuilt/darwin-x86/bin/clang++ -MMD -MP -MF ./obj/local/armeabi/objs/test/test.o.d -gcc-toolchain /Users/padlar/android/android-ndk-r10c/toolchains/arm-linux-androideabi-4.8/prebuilt/darwin