Added threading exercise

README.md

@@ -216,6 +216,7 @@ Zig Core Language
 * [X] Interfaces
 * [X] Bit manipulation
 * [X] Working with C
+* [X] Threading
 * [ ] Interfaces part 2
 
 Zig Standard Library

build.zig

@@ -1103,6 +1103,20 @@ const exercises = [_]Exercise{
         \\This little poem has 15 words!
         ,
     },
+    .{
+        .main_file = "104_threading.zig",
+        .output =
+        \\Starting work...
+        \\thread 1: started.
+        \\thread 2: started.
+        \\thread 3: started.
+        \\Some weird stuff, after starting the threads.
+        \\thread 2: finished.
+        \\thread 1: finished.
+        \\thread 3: finished.
+        \\Zig is cool!
+        ,
+    },
     .{
         .main_file = "999_the_end.zig",
         .output =

exercises/104_threading.zig

@@ -0,0 +1,129 @@
+//
+// Whenever there is a lot to calculate, the question arises as to how
+// tasks can be carried out simultaneously. We have already learned about
+// one possibility, namely asynchronous processes, in Exercises 84-91.
+//
+// However, the computing power of the processor is only distributed to
+// the started tasks, which always reaches its limits when pure computing
+// power is called up.
+//
+// For example, in blockchains based on proof of work, the miners have
+// to find a nonce for a certain character string so that the first m bits
+// in the hash of the character string and the nonce are zeros.
+// As the miner who can solve the task first receives the reward, everyone
+// tries to complete the calculations as quickly as possible.
+//
+// This is where multithreading comes into play, where tasks are actually
+// distributed across several cores of the CPU or GPU, which then really
+// means a multiplication of performance.
+//
+// The following diagram roughly illustrates the difference between the
+// various types of process execution.
+// The 'Overall Time' column is intended to illustrate how the time is
+// affected if, instead of one core as in synchronous and asynchronous
+// processing, a second core now helps to complete the work in multithreading.
+//
+// In the ideal case shown, execution takes only half the time compared
+// to the synchronous single thread. And even asynchronous processing
+// is only slightly faster in comparison.
+//
+//
+// Synchronous  Asynchronous
+// Processing   Processing        Multithreading
+// ┌──────────┐ ┌──────────┐  ┌──────────┐ ┌──────────┐
+// │ Thread 1 │ │ Thread 1 │  │ Thread 1 │ │ Thread 2 │
+// ├──────────┤ ├──────────┤  ├──────────┤ ├──────────┤    Overall Time
+// └──┼┼┼┼┼───┴─┴──┼┼┼┼┼───┴──┴──┼┼┼┼┼───┴─┴──┼┼┼┼┼───┴──┬───────┬───────┬──
+//    ├───┤        ├───┤         ├───┤        ├───┤      │       │       │
+//    │ T │        │ T │         │ T │        │ T │      │       │       │
+//    │ a │        │ a │         │ a │        │ a │      │       │       │
+//    │ s │        │ s │         │ s │        │ s │      │       │       │
+//    │ k │        │ k │         │ k │        │ k │      │       │       │
+//    │   │        │   │         │   │        │   │      │       │       │
+//    │ 1 │        │ 1 │         │ 1 │        │ 3 │      │       │       │
+//    └─┬─┘        └─┬─┘         └─┬─┘        └─┬─┘      │       │       │
+//      │            │             │            │      5 Sec     │       │
+// ┌────┴───┐      ┌─┴─┐         ┌─┴─┐        ┌─┴─┐      │       │       │
+// │Blocking│      │ T │         │ T │        │ T │      │       │       │
+// └────┬───┘      │ a │         │ a │        │ a │      │       │       │
+//      │          │ s │         │ s │        │ s │      │     8 Sec     │
+//    ┌─┴─┐        │ k │         │ k │        │ k │      │       │       │
+//    │ T │        │   │         │   │        │   │      │       │       │
+//    │ a │        │ 2 │         │ 2 │        │ 4 │      │       │       │
+//    │ s │        └─┬─┘         ├───┤        ├───┤      │       │       │
+//    │ k │          │           │┼┼┼│        │┼┼┼│      ▼       │    10 Sec
+//    │   │        ┌─┴─┐         └───┴────────┴───┴─────────     │       │
+//    │ 1 │        │ T │                                         │       │
+//    └─┬─┘        │ a │                                         │       │
+//      │          │ s │                                         │       │
+//    ┌─┴─┐        │ k │                                         │       │
+//    │ T │        │   │                                         │       │
+//    │ a │        │ 1 │                                         │       │
+//    │ s │        ├───┤                                         │       │
+//    │ k │        │┼┼┼│                                         ▼       │
+//    │   │        └───┴────────────────────────────────────────────     │
+//    │ 2 │                                                              │
+//    ├───┤                                                              │
+//    │┼┼┼│                                                              ▼
+//    └───┴────────────────────────────────────────────────────────────────
+//
+//
+// The diagram was modeled on the one in a blog in which the differences
+// between asynchronous processing and multithreading are explained in detail:
+// https://blog.devgenius.io/multi-threading-vs-asynchronous-programming-what-is-the-difference-3ebfe1179a5
+//
+// Our exercise is essentially about clarifying the approach in Zig and
+// therefore we try to keep it as simple as possible.
+// Multithreading in itself is already difficult enough. ;-)
+//
+const std = @import("std");
+
+pub fn main() !void {
+    // This is where the preparatory work takes place
+    // before the parallel processing begins.
+    std.debug.print("Starting work...\n", .{});
+
+    // These curly brackets are very important, they are necessary
+    // to enclose the area where the threads are called.
+    // Without these brackets, the program would not wait for the
+    // end of the threads and they would continue to run beyond the
+    // end of the program.
+    {
+        // Now we start the first thread, with the number as parameter
+        const handle = try std.Thread.spawn(.{}, thread_function, .{1});
+
+        // Waits for the thread to complete,
+        // then deallocates any resources created on `spawn()`.
+        defer handle.join();
+
+        // Second thread
+        const handle2 = try std.Thread.spawn(.{}, thread_function, .{-4}); // that can't be right?
+        defer handle2.join();
+
+        // Third thread
+        const handle3 = try std.Thread.spawn(.{}, thread_function, .{3});
+        defer ??? // <-- something is missing
+
+        // After the threads have been started,
+        // they run in parallel and we can still do some work in between.
+        std.time.sleep((1) * std.time.ns_per_s);
+        std.debug.print("Some weird stuff, after starting the threads.\n", .{});
+    }
+    // After we have left the closed area, we wait until
+    // the threads have run through, if this has not yet been the case.
+    std.debug.print("Zig is cool!\n", .{});
+}
+
+// This function is started with every thread that we set up.
+// In our example, we pass the number of the thread as a parameter.
+fn thread_function(num: usize) !void {
+    std.debug.print("thread {d}: {s}\n", .{ num, "started." });
+    std.time.sleep((5 - num % 3) * std.time.ns_per_s);
+    std.debug.print("thread {d}: {s}\n", .{ num, "finished." });
+}
+// This is the easiest way to run threads in parallel.
+// In general, however, more management effort is required,
+// e.g. by setting up a pool and allowing the threads to communicate
+// with each other using semaphores.
+//
+// But that's a topic for another exercise.

patches/patches/104_threading.patch

@@ -0,0 +1,17 @@
+--- exercises/104_threading.zig	2024-03-05 09:09:04.013974229 +0100
++++ answers/104_threading.zig	2024-03-05 09:12:03.987162883 +0100
+@@ -97,12 +97,12 @@
+         defer handle.join();
+ 
+         // Second thread
+-        const handle2 = try std.Thread.spawn(.{}, thread_function, .{-4}); // that can't be right?
++        const handle2 = try std.Thread.spawn(.{}, thread_function, .{2});
+         defer handle2.join();
+ 
+         // Third thread
+         const handle3 = try std.Thread.spawn(.{}, thread_function, .{3});
+-        defer ??? // <-- something is missing
++        defer handle3.join();
+ 
+         // After the threads have been started,
+         // they run in parallel and we can still do some work in between.