memory

问题 I have written following code in C. Can we call it a tail recursive implementation? #include <stdio.h> int ackermann(unsigned int *m, unsigned int *n, unsigned int* a, int* len) { if(!*m && *len == -1) { return ++*n; } else if(!*m && *len >= 0) { ++*n; *m = a[(*len)--]; } else if(*n == 0) { --*m; *n = 1; } else { ++*len; a[*len] = *m - 1; --*n; } return ackermann(m, n, a, len); } int main() { unsigned int m=4, n=1; unsigned int a[66000]; int len = -1; for (m = 0; m <= 4; m++) for (n = 0; n <

问题 I have a long running process that allocates and releases objects constantly. Although objects are being freed, the RSS mem usage goes up over time. How can I calculate how much fragmentation is happening? One possibility is to calculate RSS / sum_of_allocations and take that as an indicator. even then, how to do I calculate the denominator (sum_of_allocations). 回答1: Check out the Garbage Collector interface, gc. http://docs.python.org/2/library/gc.html You can inspect the objects are being

问题 I'm trying to do a parallel reduction to sum an array in CUDA. Currently i pass an array in which to store the sum of the elements in each block. This is my code: #include <cstdlib> #include <iostream> #include <cuda.h> #include <cuda_runtime_api.h> #include <helper_cuda.h> #include <host_config.h> #define THREADS_PER_BLOCK 256 #define CUDA_ERROR_CHECK(ans) { gpuAssert((ans), __FILE__, __LINE__); } using namespace std; inline void gpuAssert(cudaError_t code, char *file, int line, bool abort

问题 I'm trying to do a parallel reduction to sum an array in CUDA. Currently i pass an array in which to store the sum of the elements in each block. This is my code: #include <cstdlib> #include <iostream> #include <cuda.h> #include <cuda_runtime_api.h> #include <helper_cuda.h> #include <host_config.h> #define THREADS_PER_BLOCK 256 #define CUDA_ERROR_CHECK(ans) { gpuAssert((ans), __FILE__, __LINE__); } using namespace std; inline void gpuAssert(cudaError_t code, char *file, int line, bool abort

问题 A class is composed normally of member variables & methods. When we create instance of a class, memory is allocated for member variables of a class. Does member methods also occupy memory? Where are these methods stored? 回答1: Say we have the following class: public class Person { public string Name { get; set; } public Person(string name) { Name = name; } public string SayName() { string hello = "Hello! My name is "; return hello + name; } } Person p = new Person("John"); string yourName = p

问题 A class is composed normally of member variables & methods. When we create instance of a class, memory is allocated for member variables of a class. Does member methods also occupy memory? Where are these methods stored? 回答1: Say we have the following class: public class Person { public string Name { get; set; } public Person(string name) { Name = name; } public string SayName() { string hello = "Hello! My name is "; return hello + name; } } Person p = new Person("John"); string yourName = p

问题 I have JSON data that I am reading into a data frame with several fields, repartitioning it based on two columns, and converting to Pandas. This job keeps failing on EMR on just 600,000 rows of data with some obscure errors. I have also increased memory settings of the spark driver, and still don't see any resolution. Here is my pyspark code: enhDataDf = ( sqlContext .read.json(sys.argv[1]) ) enhDataDf = ( enhDataDf .repartition('column1', 'column2') .toPandas() ) enhDataDf = sqlContext

问题 I have JSON data that I am reading into a data frame with several fields, repartitioning it based on two columns, and converting to Pandas. This job keeps failing on EMR on just 600,000 rows of data with some obscure errors. I have also increased memory settings of the spark driver, and still don't see any resolution. Here is my pyspark code: enhDataDf = ( sqlContext .read.json(sys.argv[1]) ) enhDataDf = ( enhDataDf .repartition('column1', 'column2') .toPandas() ) enhDataDf = sqlContext

问题 This may be a duplicate and I apologies if that is so but I really want a definitive answer as that seems to change depending upon where I look. Is it acceptable to say that a gigabyte is 1024 megabytes or should it be said that it is 1000 megabytes? I am taking computer science at GCSE and a typical exam question could be how many bytes in a kilobyte and I believe the exam board, AQA, has the answer for such a question as 1024 not 1000. How is this? Are both correct? Which one should I go

问题 This may be a duplicate and I apologies if that is so but I really want a definitive answer as that seems to change depending upon where I look. Is it acceptable to say that a gigabyte is 1024 megabytes or should it be said that it is 1000 megabytes? I am taking computer science at GCSE and a typical exam question could be how many bytes in a kilobyte and I believe the exam board, AQA, has the answer for such a question as 1024 not 1000. How is this? Are both correct? Which one should I go