Add support for f32, as well as f64

Cargo.toml

@@ -10,6 +10,8 @@ keywords = ["quantum", "fft", "discrete", "fourier", "transform"]
 categories = ["algorithms", "compression", "science"]
 exclude = ["assets", "scripts", "benches"]
 
+[dependencies]
+num-traits = "0.2.18"
 
 [dev-dependencies]
 utilities = { path = "utilities" }
@@ -23,3 +25,4 @@ panic = "abort"
 [profile.profiling]
 inherits = "release"
 debug = true
+

README.md

@@ -58,14 +58,16 @@ including [RustFFT](https://crates.io/crates/rustfft/), while using significantl
 ### Rust
 
 ```rust
-use phastft::planner::Direction;
-use phastft::fft;
+use phastft::{
+    planner::Direction,
+    fft_64
+};
 
 fn main() {
     let big_n = 1 << 10;
     let mut reals: Vec<f64> = (1..=big_n).map(|i| i as f64).collect();
     let mut imags: Vec<f64> = (1..=big_n).map(|i| i as f64).collect();
-    fft(&mut reals, &mut imags, Direction::Forward);
+    fft_64(&mut reals, &mut imags, Direction::Forward);
 }
 ```
 

examples/benchmark.rs

@@ -3,17 +3,17 @@ use std::str::FromStr;
 
 use utilities::gen_random_signal;
 
-use phastft::fft;
+use phastft::fft_64;
 use phastft::planner::Direction;
 
-fn benchmark_fft(n: usize) {
+fn benchmark_fft_64(n: usize) {
     let big_n = 1 << n;
     let mut reals = vec![0.0; big_n];
     let mut imags = vec![0.0; big_n];
     gen_random_signal(&mut reals, &mut imags);
 
     let now = std::time::Instant::now();
-    fft(&mut reals, &mut imags, Direction::Forward);
+    fft_64(&mut reals, &mut imags, Direction::Forward);
     let elapsed = now.elapsed().as_micros();
     println!("{elapsed}");
 }
@@ -24,5 +24,5 @@ fn main() {
 
     let n = usize::from_str(&args[1]).unwrap();
 
-    benchmark_fft(n);
+    benchmark_fft_64(n);
 }

examples/profile.rs

@@ -1,14 +1,14 @@
 use std::env;
 use std::str::FromStr;
 
-use phastft::fft;
+use phastft::fft_64;
 use phastft::planner::Direction;
 
 fn benchmark_fft(num_qubits: usize) {
     let n = 1 << num_qubits;
     let mut reals: Vec<f64> = (1..=n).map(|i| i as f64).collect();
     let mut imags: Vec<f64> = (1..=n).map(|i| i as f64).collect();
-    fft(&mut reals, &mut imags, Direction::Forward);
+    fft_64(&mut reals, &mut imags, Direction::Forward);
 }
 
 fn main() {

src/cobra.rs

@@ -13,7 +13,8 @@
 //! Symposium on Foundations of Computer Science (Cat. No.98CB36280), Palo Alto, CA, USA, 1998, pp. 544-553, doi:
 //! 10.1109/SFCS.1998.743505.
 //! keywords: {Read-write memory;Costs;Computer science;Drives;Random access memory;Argon;Registers;Read only memory;Computational modeling;Libraries}
-use crate::kernels::Float;
+
+use num_traits::Float;
 
 const BLOCK_WIDTH: usize = 128;
 // size of the cacheline
@@ -78,7 +79,7 @@ pub(crate) fn bit_rev<T>(buf: &mut [T], log_n: usize) {
     since = "0.1.0",
     note = "Please use COBRA for a cache-optimal bit reverse permutation."
 )]
-fn complex_bit_rev(reals: &mut [Float], imags: &mut [Float], log_n: usize) {
+fn complex_bit_rev<T: Float>(reals: &mut [T], imags: &mut [T], log_n: usize) {
     let mut nodd: usize;
     let mut noddrev; // to hold bitwise negated or odd values
 
@@ -129,25 +130,6 @@ fn complex_bit_rev(reals: &mut [Float], imags: &mut [Float], log_n: usize) {
     }
 }
 
-/// Run in-place bit reversal on the entire state, in parallel.
-/// This function uses 2 threads to run a bit reverse on the reals buffer on one thread, and the other thread handles
-/// the bit reversal of the imaginaries buffer
-#[allow(dead_code)]
-#[deprecated(
-    since = "0.1.0",
-    note = "Naive bit reverse permutation is slow and not cache friendly. COBRA should be used instead."
-)]
-pub(crate) fn bit_reverse_permute_state_par(
-    reals: &mut [Float],
-    imags: &mut [Float],
-    log_n: usize,
-) {
-    std::thread::scope(|s| {
-        s.spawn(|| bit_rev(reals, log_n));
-        s.spawn(|| bit_rev(imags, log_n));
-    });
-}
-
 #[allow(dead_code)]
 #[deprecated(
     since = "0.1.0",
@@ -333,26 +315,6 @@ mod tests {
         }
     }
 
-    #[test]
-    fn jennifer_method_parallel() {
-        for n in 2..24 {
-            let big_n = 1 << n;
-            let mut actual_re: Vec<f64> = (0..big_n).map(f64::from).collect();
-            let mut actual_im: Vec<f64> = (0..big_n).map(f64::from).collect();
-
-            #[allow(deprecated)]
-            bit_reverse_permute_state_par(&mut actual_re, &mut actual_im, n);
-
-            let input_re: Vec<f64> = (0..big_n).map(f64::from).collect();
-            let expected_re = top_down_bit_reverse_permutation(&input_re);
-            assert_eq!(actual_re, expected_re);
-
-            let input_im: Vec<f64> = (0..big_n).map(f64::from).collect();
-            let expected_im = top_down_bit_reverse_permutation(&input_im);
-            assert_eq!(actual_im, expected_im);
-        }
-    }
-
     #[test]
     fn naive_bit_reverse_permutation() {
         for n in 2..24 {

src/kernels.rs

@@ -1,56 +1,61 @@
-use std::simd::f64x8;
-
-pub type Float = f64;
-
-pub(crate) fn fft_chunk_n_simd(
-    reals: &mut [Float],
-    imags: &mut [Float],
-    twiddles_re: &[Float],
-    twiddles_im: &[Float],
-    dist: usize,
-) {
-    let chunk_size = dist << 1;
-    assert!(chunk_size >= 16);
-
-    reals
-        .chunks_exact_mut(chunk_size)
-        .zip(imags.chunks_exact_mut(chunk_size))
-        .for_each(|(reals_chunk, imags_chunk)| {
-            let (reals_s0, reals_s1) = reals_chunk.split_at_mut(dist);
-            let (imags_s0, imags_s1) = imags_chunk.split_at_mut(dist);
-
-            reals_s0
-                .chunks_exact_mut(8)
-                .zip(reals_s1.chunks_exact_mut(8))
-                .zip(imags_s0.chunks_exact_mut(8))
-                .zip(imags_s1.chunks_exact_mut(8))
-                .zip(twiddles_re.chunks_exact(8))
-                .zip(twiddles_im.chunks_exact(8))
-                .for_each(|(((((re_s0, re_s1), im_s0), im_s1), w_re), w_im)| {
-                    let real_c0 = f64x8::from_slice(re_s0);
-                    let real_c1 = f64x8::from_slice(re_s1);
-                    let imag_c0 = f64x8::from_slice(im_s0);
-                    let imag_c1 = f64x8::from_slice(im_s1);
-
-                    let tw_re = f64x8::from_slice(w_re);
-                    let tw_im = f64x8::from_slice(w_im);
-
-                    re_s0.copy_from_slice((real_c0 + real_c1).as_array());
-                    im_s0.copy_from_slice((imag_c0 + imag_c1).as_array());
-                    let v_re = real_c0 - real_c1;
-                    let v_im = imag_c0 - imag_c1;
-                    re_s1.copy_from_slice((v_re * tw_re - v_im * tw_im).as_array());
-                    im_s1.copy_from_slice((v_re * tw_im + v_im * tw_re).as_array());
+use std::simd::{f32x16, f64x8};
+
+use num_traits::Float;
+
+macro_rules! fft_butterfly_n_simd {
+    ($func_name:ident, $precision:ty, $lanes:literal, $simd_vector:ty) => {
+        pub fn $func_name(
+            reals: &mut [$precision],
+            imags: &mut [$precision],
+            twiddles_re: &[$precision],
+            twiddles_im: &[$precision],
+            dist: usize,
+        ) {
+            let chunk_size = dist << 1;
+            assert!(chunk_size >= $lanes * 2);
+            reals
+                .chunks_exact_mut(chunk_size)
+                .zip(imags.chunks_exact_mut(chunk_size))
+                .for_each(|(reals_chunk, imags_chunk)| {
+                    let (reals_s0, reals_s1) = reals_chunk.split_at_mut(dist);
+                    let (imags_s0, imags_s1) = imags_chunk.split_at_mut(dist);
+
+                    reals_s0
+                        .chunks_exact_mut($lanes)
+                        .zip(reals_s1.chunks_exact_mut($lanes))
+                        .zip(imags_s0.chunks_exact_mut($lanes))
+                        .zip(imags_s1.chunks_exact_mut($lanes))
+                        .zip(twiddles_re.chunks_exact($lanes))
+                        .zip(twiddles_im.chunks_exact($lanes))
+                        .for_each(|(((((re_s0, re_s1), im_s0), im_s1), w_re), w_im)| {
+                            let real_c0 = <$simd_vector>::from_slice(re_s0);
+                            let real_c1 = <$simd_vector>::from_slice(re_s1);
+                            let imag_c0 = <$simd_vector>::from_slice(im_s0);
+                            let imag_c1 = <$simd_vector>::from_slice(im_s1);
+
+                            let tw_re = <$simd_vector>::from_slice(w_re);
+                            let tw_im = <$simd_vector>::from_slice(w_im);
+
+                            re_s0.copy_from_slice((real_c0 + real_c1).as_array());
+                            im_s0.copy_from_slice((imag_c0 + imag_c1).as_array());
+                            let v_re = real_c0 - real_c1;
+                            let v_im = imag_c0 - imag_c1;
+                            re_s1.copy_from_slice((v_re * tw_re - v_im * tw_im).as_array());
+                            im_s1.copy_from_slice((v_re * tw_im + v_im * tw_re).as_array());
+                        });
                 });
-        });
+        }
+    };
 }
 
-// TODO(saveliy): parallelize
-pub(crate) fn fft_chunk_n(
-    reals: &mut [Float],
-    imags: &mut [Float],
-    twiddles_re: &[Float],
-    twiddles_im: &[Float],
+fft_butterfly_n_simd!(fft_64_chunk_n_simd, f64, 8, f64x8);
+fft_butterfly_n_simd!(fft_32_chunk_n_simd, f32, 16, f32x16);
+
+pub(crate) fn fft_chunk_n<T: Float>(
+    reals: &mut [T],
+    imags: &mut [T],
+    twiddles_re: &[T],
+    twiddles_im: &[T],
     dist: usize,
 ) {
     let chunk_size = dist << 1;
@@ -79,14 +84,14 @@ pub(crate) fn fft_chunk_n(
                     *im_s0 = imag_c0 + imag_c1;
                     let v_re = real_c0 - real_c1;
                     let v_im = imag_c0 - imag_c1;
-                    *re_s1 = v_re * w_re - v_im * w_im;
-                    *im_s1 = v_re * w_im + v_im * w_re;
+                    *re_s1 = v_re * *w_re - v_im * *w_im;
+                    *im_s1 = v_re * *w_im + v_im * *w_re;
                 });
         });
 }
 
 /// `chunk_size == 4`, so hard code twiddle factors
-pub(crate) fn fft_chunk_4(reals: &mut [Float], imags: &mut [Float]) {
+pub(crate) fn fft_chunk_4<T: Float>(reals: &mut [T], imags: &mut [T]) {
     let dist = 2;
     let chunk_size = dist << 1;
 
@@ -120,7 +125,7 @@ pub(crate) fn fft_chunk_4(reals: &mut [Float], imags: &mut [Float]) {
 }
 
 /// `chunk_size == 2`, so skip phase
-pub(crate) fn fft_chunk_2(reals: &mut [Float], imags: &mut [Float]) {
+pub(crate) fn fft_chunk_2<T: Float>(reals: &mut [T], imags: &mut [T]) {
     reals
         .chunks_exact_mut(2)
         .zip(imags.chunks_exact_mut(2))