{"id":4848,"date":"2016-08-09T05:54:53","date_gmt":"2016-08-09T05:54:53","guid":{"rendered":"https:\/\/www.modernescpp.com\/index.php\/ongoing-optimization-locks\/"},"modified":"2023-06-26T12:47:06","modified_gmt":"2023-06-26T12:47:06","slug":"ongoing-optimization-locks","status":"publish","type":"post","link":"https:\/\/www.modernescpp.com\/index.php\/ongoing-optimization-locks\/","title":{"rendered":"Ongoing Optimization: Locks and Volatile with CppMem"},"content":{"rendered":"

The easiest way to solve the undefined behaviour in the post Ongoing Optimization: Unsynchronized access<\/a> is, to use a lock.<\/a><\/p>\n

<\/p>\n

Locks<\/h2>\n

Both threads thread1<\/span> and thread2<\/span> use the same mutex, wrapped in a std::lock_guard.<\/a><\/p>\n

<\/p>\n

\n\n\n\n
\n
 1\r\n 2\r\n 3\r\n 4\r\n 5\r\n 6\r\n 7\r\n 8\r\n 9\r\n10\r\n11\r\n12\r\n13\r\n14\r\n15\r\n16\r\n17\r\n18\r\n19\r\n20\r\n21\r\n22\r\n23\r\n24\r\n25\r\n26\r\n27\r\n28\r\n29<\/pre>\n<\/td>\n
\n
\/\/ ongoingOptimizationLock.cpp<\/span>\r\n\r\n#include <iostream><\/span>\r\n#include <mutex><\/span>\r\n#include <thread><\/span>\r\n\r\nint<\/span> x= 0;\r\nint<\/span> y= 0;\r\n\r\nstd::mutex mut;\r\n\r\nvoid<\/span> writing(){\r\n  std::lock_guard<std::mutex> guard(mut);\r\n  x= 2000;\r\n  y= 11;\r\n}\r\n\r\nvoid<\/span> reading(){\r\n  std::lock_guard<std::mutex> guard(mut);\r\n  std::cout << \"y: \"<\/span> << y << \" \"<\/span>;\r\n  std::cout << \"x: \"<\/span> << x << std::endl;\r\n}\r\n\r\nint<\/span> main(){\r\n  std::thread<\/span> thread1(writing);\r\n  std::thread<\/span> thread2(reading);\r\n  thread1.join();\r\n  thread2.join();\r\n};\r\n<\/pre>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
 <\/p>\n
Now, the program is well defined. Either thread1<\/span> or thread2<\/span> is running. Dependent on that, either both values are or aren’t set. So the following values for x and y are possible.<\/p>\n
 \"sukzessiveOptimierungLocksEng\"<\/p>\n
CppMem<\/h3>\n
I didn’t achieve it to use std::lock_guard in CppMem. Sorry. But if you achieve it, let me know. <\/p>\n
That was easy. But the synchronization with locks is too heavyweight. The freedom of the system to optimize the program is drastically reduced. There are only two possibilities. So, what should I do next? Of course, switch to atomics. <\/p>\n
There is the volatile<\/span> keyword in C++. Let’s try it out.<\/p>\n<\/p>\n
volatile<\/h2>\n
What has the keyword volatile<\/span> in C# and Java with the keyword volatile<\/span> in C++ in common? Nothing!<\/strong><\/p>\n
It’s so easy in C++.<\/p>\n
    \n
  1. volatile<\/span> is for special objects on which optimized read or write operations are not allowed.<\/li>\n
  2. std::atomic<\/span> defines atomic variables meant for thread-safe reading and writing.<\/li>\n<\/ol>\n
    It’s so easy, but. The confusion starts exactly here. The keyword volatile<\/span> in Java and C# means std::atomic<\/span> in C++. Or, to say if differently. volatile<\/span> has no multithreading semantics in C++. <\/p>\n
    volatile<\/span> is typically used in embedded programming to denote objects, which can change independent of the regular program flow. These are for example objects, which represent an external device (memory-mapped I\/O). Because these objects can change independently of the regular program flow, their value will directly be written in the main memory. So there is no optimized storing in caches.<\/p>\n
    <\/p>\n
    \n\n\n\n
    \n
     1\r\n 2\r\n 3\r\n 4\r\n 5\r\n 6\r\n 7\r\n 8\r\n 9\r\n10\r\n11\r\n12\r\n13\r\n14\r\n15\r\n16\r\n17\r\n18\r\n19\r\n20\r\n21\r\n22\r\n23\r\n24<\/pre>\n<\/td>\n
    		\n
    \/\/ ongoingOptimizationVolatile.cpp<\/span>\r\n\r\n#include <iostream><\/span>\r\n#include <thread><\/span>\r\n\r\nvolatile<\/span> int<\/span> x= 0;\r\nvolatile<\/span> int<\/span> y= 0;\r\n\r\nvoid<\/span> writing(){\r\n  x= 2000;\r\n  y= 11;\r\n}\r\n\r\nvoid<\/span> reading(){ \r\n  std::cout << \"y: \"<\/span> << y << \" \"<\/span>;\r\n  std::cout << \"x: \"<\/span> << x << std::endl;\r\n}\r\n\r\nint<\/span> main(){\r\n  std::thread<\/span> thread1(writing);\r\n  std::thread<\/span> thread2(reading);\r\n  thread1.join();\r\n  thread2.join();\r\n};\r\n<\/pre>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
     <\/p>\n
    So what does that mean for our small program from Ongoing Optimization<\/a> if I declare the int variables as volatile<\/span>? I guess you know it. The program has a data race <\/a>on the variables x and y. So the program has undefined behavior and I can not reason about x and y.<\/p>\n
    \"undefinedEng\"<\/p>\n
    CppMem<\/h3>\n
    volatile has no multithreading semantics. This shows CppMem unambiguously.<\/p>\n
     <\/p>\n
    \n\n\n\n
    \n
     1\r\n 2\r\n 3\r\n 4\r\n 5\r\n 6\r\n 7\r\n 8\r\n 9\r\n10\r\n11\r\n12\r\n13<\/pre>\n<\/td>\n
    		\n
    int<\/span> main(){\r\n  volatile<\/span> int<\/span> x= 0; \r\n  volatile<\/span> int<\/span> y= 0;\r\n  {{{ { \r\n      x= 2000; \r\n      y= 11;\r\n      }\r\n  ||| {\r\n      y;\r\n      x;\r\n      } \r\n  }}}\r\n}\r\n<\/pre>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
     <\/p>\n
    The results are identical to the results of my analysis in the unsynchronized assessment with non-atomics. So you can read it here in my last post Ongoing Optimization: Unsynchronized access with CppMem.<\/a> It makes no difference if you use the variables x and y with or without the volatile<\/span> qualifier.  <\/a><\/p>\n
    What’s next?<\/h2>\n
    In the next pos<\/a>t, I will make it right. I use atomics with sequential consistency.<\/p>\n
     <\/p>\n
     <\/p>\n
     <\/p>\n
     <\/p>\n","protected":false},"excerpt":{"rendered":"
    The easiest way to solve the undefined behaviour in the post Ongoing Optimization: Unsynchronized access is, to use a lock.<\/p>\n","protected":false},"author":21,"featured_media":4847,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[369],"tags":[486,430,521,457],"class_list":["post-4848","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-multithreading-application","tag-cppmem","tag-lock","tag-ongoing-optimization","tag-volatile"],"_links":{"self":[{"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/posts\/4848","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/users\/21"}],"replies":[{"embeddable":true,"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/comments?post=4848"}],"version-history":[{"count":1,"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/posts\/4848\/revisions"}],"predecessor-version":[{"id":6957,"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/posts\/4848\/revisions\/6957"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/media\/4847"}],"wp:attachment":[{"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/media?parent=4848"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/categories?post=4848"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.modernescpp.com\/index.php\/wp-json\/wp\/v2\/tags?post=4848"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}