From the documentation on parfor: The body of a parfor-loop cannot contain global or persistent variable declarations. In the context of your problem, i.e., calling a function within the parfor that in turn references a global, this translates into: “parfor will probably not give expected or meaningful results”. This makes perfect sense. Consider the following … Read more
You can do something like this nvcc -arch=sm_35 -rdc=true simple1.cu -o simple1 -lcudadevrt or If you have 2 files simple1.cu and test.c then you can do something as below. This is called seperate compilation. nvcc -arch=sm_35 -dc simple1.cu nvcc -arch=sm_35 -dlink simple1.o -o link.o -lcudadevrt g++ -c test.c g++ link.o simple1.o test.o -o simple -L/usr/local/cuda/lib64/ … Read more
You should use reduction like this: #pragma omp parallel for reduction (+:sum) for (int i=0;i<n;i++) sum=sum+a[i];
Well – best practice is that structs should always (except in a few very specific scenarios, and even then at risk) be immutable. And immutable data is always thread safe. So if you followed best practice and made this: struct Data { readonly int _number; public int Number { get { return _number; } } … Read more
The standard approach here is to separate the selection of a type from the use of the type: the latter takes the form of a function template instantiated several times by the former non-template function (or function template with fewer template parameters). To avoid duplicating the normal parameters between these two layers, use a generic … Read more
What you are asking for is a classic parallel algorithm called stream compaction1. If Thrust is an option, you may simply use thrust::copy_if. This is a stable algorithm, it preserves relative order of all elements. Rough sketch: #include <thrust/copy.h> template<typename T> struct is_non_zero { __host__ __device__ auto operator()(T x) const -> bool { return x … Read more
This is how make is defined to work. A rule like this: foo bar baz : boz ; $(BUILDIT) is exactly equivalent, to make, to writing these three rules: foo : boz ; $(BUILDIT) bar : boz ; $(BUILDIT) baz : boz ; $(BUILDIT) There is no way (in GNU make) to define an explicit … Read more
Current Stream API implementation uses collector combiner to combine the intermediate results in exactly the same way as they were previously split. Also the splitting strategy depends on the source and common pool parallelism level, but does not depend on exact reduction operation used (the same for reduce, collect, forEach, count, etc.). Relying on this … Read more
The problem is that the rather limited parallelism you have configured is eaten up by the outer stream processing: if you say that you want eight threads and process a stream of more than eight items with parallel() it will create eight worker threads and let them process items. Then within your consumer you are … Read more
You’re not leveraging any async I/O APIs in any of your code. Everything you’re doing is CPU bound and all your I/O operations are going to waste CPU resources blocking. AsParallel is for compute bound tasks, if you want to take advantage of async I/O you need to leverage the Asynchronous Programming Model (APM) based … Read more