sad/raptorq
1
0
Fork 0
mirror of https://github.com/cberner/raptorq.git synced 2024-06-27 09:19:02 +00:00
Code Issues Packages Projects Releases Wiki Activity

Optimize first phase to call ones_in_column() only once for r = 1 case

Browse Source
This commit is contained in:
Christopher Berner 2020-12-26 20:25:16 -08:00
parent 602fc8711d
commit 24235dd213
2 changed files with 63 additions and 47 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

80
README.md
View File

@ -23,51 +23,51 @@ The following were run on an Intel Core i5-6600K @ 3.50GHz
```
Symbol size: 1280 bytes (without pre-built plan)
symbol count = 10, encoded 127 MB in 0.483secs, throughput: 2119.9Mbit/s
symbol count = 100, encoded 127 MB in 0.480secs, throughput: 2132.2Mbit/s
symbol count = 250, encoded 127 MB in 0.458secs, throughput: 2233.5Mbit/s
symbol count = 500, encoded 127 MB in 0.466secs, throughput: 2189.9Mbit/s
symbol count = 1000, encoded 126 MB in 0.474secs, throughput: 2142.7Mbit/s
symbol count = 2000, encoded 126 MB in 0.542secs, throughput: 1873.8Mbit/s
symbol count = 5000, encoded 122 MB in 0.571secs, throughput: 1710.3Mbit/s
symbol count = 10000, encoded 122 MB in 0.682secs, throughput: 1431.9Mbit/s
symbol count = 20000, encoded 122 MB in 0.901secs, throughput: 1083.9Mbit/s
symbol count = 50000, encoded 122 MB in 1.348secs, throughput: 724.5Mbit/s
symbol count = 10, encoded 127 MB in 0.478secs, throughput: 2142.1Mbit/s
symbol count = 100, encoded 127 MB in 0.443secs, throughput: 2310.2Mbit/s
symbol count = 250, encoded 127 MB in 0.444secs, throughput: 2303.9Mbit/s
symbol count = 500, encoded 127 MB in 0.428secs, throughput: 2384.4Mbit/s
symbol count = 1000, encoded 126 MB in 0.459secs, throughput: 2212.7Mbit/s
symbol count = 2000, encoded 126 MB in 0.487secs, throughput: 2085.5Mbit/s
symbol count = 5000, encoded 122 MB in 0.562secs, throughput: 1737.7Mbit/s
symbol count = 10000, encoded 122 MB in 0.637secs, throughput: 1533.1Mbit/s
symbol count = 20000, encoded 122 MB in 0.868secs, throughput: 1125.1Mbit/s
symbol count = 50000, encoded 122 MB in 1.236secs, throughput: 790.1Mbit/s
Symbol size: 1280 bytes (with pre-built plan)
symbol count = 10, encoded 127 MB in 0.238secs, throughput: 4302.2Mbit/s
symbol count = 100, encoded 127 MB in 0.151secs, throughput: 6777.7Mbit/s
symbol count = 250, encoded 127 MB in 0.167secs, throughput: 6125.4Mbit/s
symbol count = 500, encoded 127 MB in 0.174secs, throughput: 5865.0Mbit/s
symbol count = 1000, encoded 126 MB in 0.191secs, throughput: 5317.4Mbit/s
symbol count = 2000, encoded 126 MB in 0.226secs, throughput: 4493.9Mbit/s
symbol count = 5000, encoded 122 MB in 0.258secs, throughput: 3785.1Mbit/s
symbol count = 10000, encoded 122 MB in 0.336secs, throughput: 2906.4Mbit/s
symbol count = 20000, encoded 122 MB in 0.428secs, throughput: 2281.7Mbit/s
symbol count = 50000, encoded 122 MB in 0.603secs, throughput: 1619.5Mbit/s
symbol count = 10, encoded 127 MB in 0.226secs, throughput: 4530.6Mbit/s
symbol count = 100, encoded 127 MB in 0.150secs, throughput: 6822.9Mbit/s
symbol count = 250, encoded 127 MB in 0.165secs, throughput: 6199.7Mbit/s
symbol count = 500, encoded 127 MB in 0.168secs, throughput: 6074.5Mbit/s
symbol count = 1000, encoded 126 MB in 0.184secs, throughput: 5519.7Mbit/s
symbol count = 2000, encoded 126 MB in 0.200secs, throughput: 5078.1Mbit/s
symbol count = 5000, encoded 122 MB in 0.249secs, throughput: 3921.9Mbit/s
symbol count = 10000, encoded 122 MB in 0.339secs, throughput: 2880.7Mbit/s
symbol count = 20000, encoded 122 MB in 0.426secs, throughput: 2292.4Mbit/s
symbol count = 50000, encoded 122 MB in 0.585secs, throughput: 1669.3Mbit/s
Symbol size: 1280 bytes
symbol count = 10, decoded 127 MB in 0.727secs using 0.0% overhead, throughput: 1408.4Mbit/s
symbol count = 100, decoded 127 MB in 0.598secs using 0.0% overhead, throughput: 1711.4Mbit/s
symbol count = 250, decoded 127 MB in 0.570secs using 0.0% overhead, throughput: 1794.6Mbit/s
symbol count = 500, decoded 127 MB in 0.572secs using 0.0% overhead, throughput: 1784.1Mbit/s
symbol count = 1000, decoded 126 MB in 0.600secs using 0.0% overhead, throughput: 1692.7Mbit/s
symbol count = 2000, decoded 126 MB in 0.652secs using 0.0% overhead, throughput: 1557.7Mbit/s
symbol count = 5000, decoded 122 MB in 0.719secs using 0.0% overhead, throughput: 1358.2Mbit/s
symbol count = 10000, decoded 122 MB in 0.866secs using 0.0% overhead, throughput: 1127.7Mbit/s
symbol count = 20000, decoded 122 MB in 1.085secs using 0.0% overhead, throughput: 900.1Mbit/s
symbol count = 50000, decoded 122 MB in 1.566secs using 0.0% overhead, throughput: 623.6Mbit/s
symbol count = 10, decoded 127 MB in 0.671secs using 0.0% overhead, throughput: 1526.0Mbit/s
symbol count = 100, decoded 127 MB in 0.526secs using 0.0% overhead, throughput: 1945.7Mbit/s
symbol count = 250, decoded 127 MB in 0.526secs using 0.0% overhead, throughput: 1944.8Mbit/s
symbol count = 500, decoded 127 MB in 0.504secs using 0.0% overhead, throughput: 2024.8Mbit/s
symbol count = 1000, decoded 126 MB in 0.517secs using 0.0% overhead, throughput: 1964.5Mbit/s
symbol count = 2000, decoded 126 MB in 0.575secs using 0.0% overhead, throughput: 1766.3Mbit/s
symbol count = 5000, decoded 122 MB in 0.638secs using 0.0% overhead, throughput: 1530.7Mbit/s
symbol count = 10000, decoded 122 MB in 0.784secs using 0.0% overhead, throughput: 1245.6Mbit/s
symbol count = 20000, decoded 122 MB in 0.987secs using 0.0% overhead, throughput: 989.4Mbit/s
symbol count = 50000, decoded 122 MB in 1.472secs using 0.0% overhead, throughput: 663.4Mbit/s
symbol count = 10, decoded 127 MB in 0.711secs using 5.0% overhead, throughput: 1440.1Mbit/s
symbol count = 100, decoded 127 MB in 0.610secs using 5.0% overhead, throughput: 1677.8Mbit/s
symbol count = 250, decoded 127 MB in 0.596secs using 5.0% overhead, throughput: 1716.4Mbit/s
symbol count = 500, decoded 127 MB in 0.574secs using 5.0% overhead, throughput: 1777.9Mbit/s
symbol count = 1000, decoded 126 MB in 0.630secs using 5.0% overhead, throughput: 1612.1Mbit/s
symbol count = 2000, decoded 126 MB in 0.653secs using 5.0% overhead, throughput: 1555.3Mbit/s
symbol count = 5000, decoded 122 MB in 0.781secs using 5.0% overhead, throughput: 1250.4Mbit/s
symbol count = 10000, decoded 122 MB in 0.994secs using 5.0% overhead, throughput: 982.5Mbit/s
symbol count = 20000, decoded 122 MB in 1.318secs using 5.0% overhead, throughput: 740.9Mbit/s
symbol count = 50000, decoded 122 MB in 2.182secs using 5.0% overhead, throughput: 447.6Mbit/s
symbol count = 10, decoded 127 MB in 0.654secs using 5.0% overhead, throughput: 1565.6Mbit/s
symbol count = 100, decoded 127 MB in 0.537secs using 5.0% overhead, throughput: 1905.8Mbit/s
symbol count = 250, decoded 127 MB in 0.540secs using 5.0% overhead, throughput: 1894.4Mbit/s
symbol count = 500, decoded 127 MB in 0.509secs using 5.0% overhead, throughput: 2004.9Mbit/s
symbol count = 1000, decoded 126 MB in 0.543secs using 5.0% overhead, throughput: 1870.4Mbit/s
symbol count = 2000, decoded 126 MB in 0.575secs using 5.0% overhead, throughput: 1766.3Mbit/s
symbol count = 5000, decoded 122 MB in 0.665secs using 5.0% overhead, throughput: 1468.5Mbit/s
symbol count = 10000, decoded 122 MB in 0.830secs using 5.0% overhead, throughput: 1176.6Mbit/s
symbol count = 20000, decoded 122 MB in 1.048secs using 5.0% overhead, throughput: 931.8Mbit/s
symbol count = 50000, decoded 122 MB in 1.740secs using 5.0% overhead, throughput: 561.2Mbit/s
```
### Public API

30
src/pi_solver.rs
View File

@ -152,6 +152,8 @@ impl FirstPhaseRowSelectionStats {
end_row: usize,
start_col: usize,
end_col: usize,
// Ones from start_row to end_row, i.e. matrix.get_ones_in_column(self.start_col, start_row, end_row)
ones_in_start_col: &[u32],
matrix: &T,
) {
// Only shrinking is supported
@ -159,8 +161,22 @@ impl FirstPhaseRowSelectionStats {
assert_eq!(self.start_row, start_row - 1);
assert_eq!(self.start_col, start_col - 1);
// Remove this separately, since it's not part of ones_in_start_col
if matrix.get(self.start_row, self.start_col) == Octet::one() {
let row = self.start_row;
self.ones_per_row.decrement(row);
let ones = self.ones_per_row.get(row);
if ones == 0 {
self.rows_with_single_one.retain(|x| *x != row);
} else if ones == 1 {
self.remove_graph_edge(row, matrix);
}
self.ones_histogram.decrement((ones + 1) as usize);
self.ones_histogram.increment(ones as usize);
}
let mut possible_new_graph_edges = vec![];
for row in matrix.get_ones_in_column(self.start_col, self.start_row, end_row) {
for &row in ones_in_start_col {
let row = row as usize;
self.ones_per_row.decrement(row);
let ones = self.ones_per_row.get(row);
@ -667,11 +683,15 @@ impl<T: BinaryMatrix> IntermediateSymbolDecoder<T> {
// because of Errata 2.
let temp_value = self.A.get(temp, temp);
let ones_in_column =
self.A
.get_ones_in_column(temp, self.i + 1, self.A.height() - num_hdpc_rows);
selection_helper.resize(
self.i + 1,
self.A.height() - self.A_hdpc_rows.as_ref().unwrap().height(),
self.i + 1,
self.A.width() - self.u - (r - 1),
&ones_in_column,
&self.A,
);
for i in 0..(r - 1) {
@ -679,12 +699,8 @@ impl<T: BinaryMatrix> IntermediateSymbolDecoder<T> {
.hint_column_dense_and_frozen(self.A.width() - self.u - 1 - i);
}
// Cloning the iterator is safe here, because we don't re-read any of the rows that
// we add to
for row in self
.A
.get_ones_in_column(temp, self.i + 1, self.A.height() - num_hdpc_rows)
{
// Skip the first element since that's the i'th row
for row in ones_in_column {
let row = row as usize;
assert_eq!(&temp_value, &Octet::one());
// Addition is equivalent to subtraction.