From bfed6600205504a3fd2e3d3922ca5da6995224a7 Mon Sep 17 00:00:00 2001 From: Chris Boesch Date: Thu, 7 Nov 2024 15:01:59 +0100 Subject: [PATCH] Fixed formating, created patch file. --- exercises/109_vectors.zig | 42 +++++++++++++++---------------- patches/patches/109_vectors.patch | 8 +++--- 2 files changed, 25 insertions(+), 25 deletions(-) diff --git a/exercises/109_vectors.zig b/exercises/109_vectors.zig index 106937e..96892ca 100644 --- a/exercises/109_vectors.zig +++ b/exercises/109_vectors.zig @@ -10,16 +10,16 @@ // These are known as "single instruction, multiple data" (SIMD) // instructions. SIMD instructions can make code significantly // more performant. -// +// // To see why, imagine we have a program in which we take the // square root of four (changing) f32 floats. -// +// // A simple compiler would take the program and produce machine code // which calculates each square root sequentially. Most registers on // modern CPUs have 64 bits, so we could imagine that each float moves // into a 64-bit register, and the following happens four times: // -// 32 bits 32 bits +// 32 bits 32 bits // +-------------------+ // register | 0 | x | // +-------------------+ @@ -35,7 +35,7 @@ // Notice that half of the register contains blank data to which // nothing happened. What a waste! What if we were able to use // that space instead? This is the idea at the core of SIMD. -// +// // Most modern CPUs contain specialized registers with at least 128 bits // for performing SIMD instructions. On a machine with 128-bit SIMD // registers, a smart compiler would probably NOT issue four sqrt @@ -50,11 +50,11 @@ // +---------------------------------------+ // register | 4.0 | 9.0 | 25.0 | 49.0 | // +---------------------------------------+ -// +// // | // [SIMD SQRT instruction] // V -// +// // +---------------------------------------+ // register | 2.0 | 3.0 | 5.0 | 7.0 | // +---------------------------------------+ @@ -74,26 +74,26 @@ // SIMD instructions, whenever possible. // // Defining vectors in Zig is straightforwards. No library import is needed. -const v1 = @Vector(3, i32) { 1, 10, 100}; -const v2 = @Vector(3, f32) {2.0, 3.0, 5.0}; +const v1 = @Vector(3, i32){ 1, 10, 100 }; +const v2 = @Vector(3, f32){ 2.0, 3.0, 5.0 }; // Vectors support the same builtin operators as their underlying base types. const v3 = v1 + v1; // { 2, 20, 200}; const v4 = v2 * v2; // { 4.0, 9.0, 25.0}; // Intrinsics that apply to base types usually extend to vectors. -const v5 : @Vector(3, f32) = @floatFromInt(v3); // { 2.0, 20.0, 200.0} -const v6 = v4 - v5; // { 2.0, -11.0, -175.0} -const v7 = @abs(v6); // { 2.0, 11.0, 175.0} +const v5: @Vector(3, f32) = @floatFromInt(v3); // { 2.0, 20.0, 200.0} +const v6 = v4 - v5; // { 2.0, -11.0, -175.0} +const v7 = @abs(v6); // { 2.0, 11.0, 175.0} // We can make constant vectors, and reduce vectors. -const v8 : @Vector(4, u8) = @splat(2); // { 2, 2, 2, 2} -const v8_sum = @reduce(.Add, v8); // 8 -const v8_min = @reduce(.Min, v8); // 2 +const v8: @Vector(4, u8) = @splat(2); // { 2, 2, 2, 2} +const v8_sum = @reduce(.Add, v8); // 8 +const v8_min = @reduce(.Min, v8); // 2 // Fixed-length arrays can be automatically assigned to vectors (and vice-versa). -const single_digit_primes = [4] i8 {2, 3, 5, 7}; -const prime_vector : @Vector(4, i8) = single_digit_primes; +const single_digit_primes = [4]i8{ 2, 3, 5, 7 }; +const prime_vector: @Vector(4, i8) = single_digit_primes; // Now let's use vectors to simplify and optimize some code! // @@ -103,8 +103,8 @@ const prime_vector : @Vector(4, i8) = single_digit_primes; // // Ewa wrote the following function to figure this out. -fn calcMaxPairwiseDiffOld( list1 : [4] f32, list2 : [4] f32) f32 { - var max_diff : f32 = 0; +fn calcMaxPairwiseDiffOld(list1: [4]f32, list2: [4]f32) f32 { + var max_diff: f32 = 0; for (list1, list2) |n1, n2| { const abs_diff = @abs(n1 - n2); if (abs_diff > max_diff) { @@ -120,7 +120,7 @@ fn calcMaxPairwiseDiffOld( list1 : [4] f32, list2 : [4] f32) f32 { // Help Ewa finish the vector version! The examples above should help. const Vec4 = @Vector(4, f32); -fn calcMaxPairwiseDiffNew( a : Vec4, b : Vec4) f32 { +fn calcMaxPairwiseDiffNew(a: Vec4, b: Vec4) f32 { const abs_diff_vec = ???; const max_diff = @reduce(???, abs_diff_vec); return max_diff; @@ -138,8 +138,8 @@ const std = @import("std"); const print = std.debug.print; pub fn main() void { - const l1 = [4] f32 { 3.141, 2.718, 0.577, 1.000}; - const l2 = [4] f32 { 3.154, 2.707, 0.591, 0.993}; + const l1 = [4]f32{ 3.141, 2.718, 0.577, 1.000 }; + const l2 = [4]f32{ 3.154, 2.707, 0.591, 0.993 }; const mpd_old = calcMaxPairwiseDiffOld(l1, l2); const mpd_new = calcMaxPairwiseDiffNew(l1, l2); print("Max difference (old fn): {d: >5.3}\n", .{mpd_old}); diff --git a/patches/patches/109_vectors.patch b/patches/patches/109_vectors.patch index 4b11da9..bf18cc0 100644 --- a/patches/patches/109_vectors.patch +++ b/patches/patches/109_vectors.patch @@ -1,12 +1,12 @@ ---- exercises/109_vectors.zig 2024-11-03 11:17:00.928652000 +1000 -+++ answers/109_vectors.zig 2024-11-07 13:11:23.838667200 +1000 +--- exercises/109_vectors.zig 2024-11-07 14:57:09.673383618 +0100 ++++ answers/109_vectors.zig 2024-11-07 14:22:59.069150138 +0100 @@ -121,8 +121,8 @@ const Vec4 = @Vector(4, f32); - fn calcMaxPairwiseDiffNew( a : Vec4, b : Vec4) f32 { + fn calcMaxPairwiseDiffNew(a: Vec4, b: Vec4) f32 { - const abs_diff_vec = ???; - const max_diff = @reduce(???, abs_diff_vec); -+ const abs_diff_vec = @abs( a - b ); ++ const abs_diff_vec = @abs(a - b); + const max_diff = @reduce(.Max, abs_diff_vec); return max_diff; }