Add the all_experiment binary and scripts
(cherry picked from commit 05e56d9a71d0933ac226c075a54c1950996984b9)
This commit is contained in:
Guillaume DIDIER
parent
856bf5e4a1
commit
ffb763bed4
7
prefetcher_reverse/run-msr-all.sh
Executable file
7
prefetcher_reverse/run-msr-all.sh
Executable file
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#!/bin/bash
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PREFETCH_MSR=$1
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sudo wrmsr -a 0x1a4 $PREFETCH_MSR
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sudo rdmsr -a 0x1a4
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cargo run --bin all_experiments --release > with-${PREFETCH_MSR}-prefetcher.log
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283
prefetcher_reverse/src/bin/all_experiments.rs
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283
prefetcher_reverse/src/bin/all_experiments.rs
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/*
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Objective : run an exploration of patterns of a length given as an arg and test all the possible ones,
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Then proceed with some analysis.
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Probably will use library functions for a lot of it
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(Auto pattern generation belongs in lib.rs, the analysis part may be a little bit more subtle)
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Output, detailed CSV, and well chosen slices + summaries ?
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Alternatively, limit to 3 accesses ?
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*/
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use cache_utils::ip_tool::{Function, TIMED_MACCESS};
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use itertools::Itertools;
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use nix::sched::sched_yield;
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use prefetcher_reverse::{
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pattern_helper, FullPageDualProbeResults, PatternAccess, Prober, PAGE_CACHELINE_LEN,
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};
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pub const NUM_ITERATION: u32 = 1 << 10;
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pub const WARMUP: u32 = 100;
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struct Params {
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limit: usize,
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same_ip: bool,
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unique_ip: bool,
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}
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fn print_tagged_csv(tag: &str, results: Vec<FullPageDualProbeResults>, len: usize) {
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// Print Header,
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println!("{}Functions:i,Addr", tag);
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if !results.is_empty() {
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let first = &results[0];
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for (i, p) in first.pattern.iter().enumerate() {
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println!("{}Functions:{},{:p}", tag, i, p.function.ip)
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}
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}
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println!(
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"{}:{}ProbeAddr,Probe_SF_H,Probe_SF_HR,Probe_SR_H,Probe_SR_HR,Probe_FF_H,Probe_FF_HR",
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tag,
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(0..len)
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.map(|i| {
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format!(
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"Offset_{i},\
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Offset_{i}_SF_H,Offset_{i}_SF_HR,\
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Offset_{i}_SR_H,Offset_{i}_SR_HR,\
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Offset_{i}_FF_H,Offset_{i}_FF_HR,",
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i = i
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)
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})
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.format(""),
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);
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// Print each line,
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// TODO : double check with the impl in lib.rs how to extract the various piece of info.
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for res in results {
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assert_eq!(res.pattern.len(), len);
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for probe_addr in 0..PAGE_CACHELINE_LEN {
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let sf_h = res.single_probe_results[probe_addr].flush.probe_result;
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let sr_h = res.single_probe_results[probe_addr].load.probe_result;
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let ff_h = res.full_flush_results.probe_result[probe_addr];
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println!(
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"{}:{}{},{},{},{},{},{},{}",
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tag,
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(0..len)
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.map(|i| {
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let sf_h = res.single_probe_results[probe_addr].flush.pattern_result[i];
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let sf_hr = sf_h as f32 / res.num_iteration as f32;
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let sr_h = res.single_probe_results[probe_addr].load.pattern_result[i];
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let sr_hr = sr_h as f32 / res.num_iteration as f32;
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let ff_h = res.full_flush_results.pattern_result[i];
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let ff_hr = ff_h as f32 / res.num_iteration as f32;
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format!(
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"{},{},{},{},{},{},{},",
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res.pattern[i].offset, sf_h, sf_hr, sr_h, sr_hr, ff_h, ff_hr
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)
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})
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.format(""),
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probe_addr,
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sf_h,
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sf_h as f32 / res.num_iteration as f32,
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sr_h,
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sr_h as f32 / res.num_iteration as f32,
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ff_h,
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ff_h as f32 / res.num_iteration as f32
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);
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}
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}
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}
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fn exp(
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i: usize,
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tag: &str,
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patterns: &Vec<Vec<usize>>,
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same_ip: bool,
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unique_ip: bool,
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prober: &mut Prober<1>,
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) {
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if same_ip {
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let single_reload = Function::try_new(1, 0, TIMED_MACCESS).unwrap();
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let mut results = Vec::new();
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for pattern in patterns {
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eprintln!("Single IP pattern: {:?}", pattern);
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let single_ip_pattern = pattern_helper(pattern, &single_reload);
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let result = prober.full_page_probe(single_ip_pattern, NUM_ITERATION, WARMUP);
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results.push(result);
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sched_yield().unwrap();
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}
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print_tagged_csv(&format!("SingleIP{}", tag), results, i);
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// generate the vec with a single IP
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}
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if unique_ip {
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let mut functions = Vec::new();
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let rounded_i = i.next_power_of_two();
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for j in 0..i {
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functions.push(Function::try_new(rounded_i, j, TIMED_MACCESS).unwrap());
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}
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let mut results = Vec::new();
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for pattern in patterns {
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eprintln!("Unique IP pattern: {:?}", pattern);
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let unique_ip_pattern = pattern
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.iter()
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.enumerate()
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.map(|(i, &offset)| PatternAccess {
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function: &functions[i],
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offset,
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})
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.collect();
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let result = prober.full_page_probe(unique_ip_pattern, NUM_ITERATION, WARMUP);
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results.push(result);
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sched_yield().unwrap();
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}
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print_tagged_csv(&format!("UniqueIPs{}", tag), results, i);
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}
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}
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/* TODO change access patterns
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- We want patterns for i,j in [0,64]^2
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A (i,i+k,j)
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B (i,i-k,j)
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C (i,j,j+k)
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D (i,j,j-k)
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with k in 1,2,3,8, plus possibly others.
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4 access patterns will probably come in later
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In addition consider base + stride + len patterns, with a well chosen set of length, strides and bases
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len to be considered 2,3,4
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Identifiers :
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E 2
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*/
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fn main() {
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// TODO Argument parsing
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let args = Params {
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limit: 2,
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same_ip: true,
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unique_ip: true,
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};
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let mut experiments: Vec<(String, usize, usize, Box<dyn Fn(usize, usize) -> Vec<usize>>)> = vec![];
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for class in [
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(
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"",
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Box::new(|k: usize| {
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let f = Box::new(move |i, j| {
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let v = vec![
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i,j,
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];
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v.truncate(k);
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v
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}) as Box<dyn Fn(usize, usize) -> Vec<usize>>;
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let i_limit = if k > 0 {
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PAGE_CACHELINE_LEN
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} else {
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1
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};
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let j_limit = if k > 1 {
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PAGE_CACHELINE_LEN
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} else {
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1
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};
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(i_limit,j_limit,f)
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}) as Box<dyn Fn(usize) -> (usize, usize, Box<dyn Fn(usize, usize) -> Vec<usize>>)>,
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),
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] {
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for k in [0,1,2] {
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let exp = class.1(k);
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experiments.push((format!("{}{}", class.0, k),exp.1, exp.2, exp.3));
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}
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}
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for class in [
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(
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"A",
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Box::new(|k| {
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Box::new(move |i, j| vec![i, (i + k) % PAGE_CACHELINE_LEN, j])
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as Box<dyn Fn(usize, usize) -> Vec<usize>>
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}) as Box<dyn Fn(usize) -> Box<dyn Fn(usize, usize) -> Vec<usize>>>,
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),
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(
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"B",
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Box::new(|k| {
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Box::new(move |i, j| vec![i, (i - k) % PAGE_CACHELINE_LEN, j])
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as Box<dyn Fn(usize, usize) -> Vec<usize>>
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}) as Box<dyn Fn(usize) -> Box<dyn Fn(usize, usize) -> Vec<usize>>>,
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),
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(
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"C",
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Box::new(|k| {
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Box::new(move |i, j| vec![i, j, (j + k) % PAGE_CACHELINE_LEN])
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as Box<dyn Fn(usize, usize) -> Vec<usize>>
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}) as Box<dyn Fn(usize) -> Box<dyn Fn(usize, usize) -> Vec<usize>>>,
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),
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(
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"D",
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Box::new(|k| {
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Box::new(move |i, j| vec![i, j, (j - k) % PAGE_CACHELINE_LEN])
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as Box<dyn Fn(usize, usize) -> Vec<usize>>
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}) as Box<dyn Fn(usize) -> Box<dyn Fn(usize, usize) -> Vec<usize>>>,
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),
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] {
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for k in [1, 2, 3, 4, 8] {
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experiments.push((format!("{}{}", class.0, k), PAGE_CACHELINE_LEN, PAGE_CACHELINE_LEN, class.1(k)));
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}
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}
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for class in [(
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"E",
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Box::new(|len: usize| {
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Box::new(move |base, stride| {
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let mut res = vec![base];
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for i in 0..len {
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res.push((base + stride * (i + 1)) % PAGE_CACHELINE_LEN)
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}
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res
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}) as Box<dyn Fn(usize, usize) -> Vec<usize>>
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}) as Box<dyn Fn(usize) -> Box<dyn Fn(usize, usize) -> Vec<usize>>>,
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)] {
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for len in [2, 3, 4] {
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experiments.push((format!("{}{}", class.0, len), PAGE_CACHELINE_LEN, PAGE_CACHELINE_LEN, class.1(len)));
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}
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}
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for class in [
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(
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"F",
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Box::new(|k: isize| {
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Box::new(move |i, j| {
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vec![
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i,
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(i as isize + k + PAGE_CACHELINE_LEN as isize) as usize
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% PAGE_CACHELINE_LEN,
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j,
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(i as isize + 2 * k + PAGE_CACHELINE_LEN as isize) as usize
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% PAGE_CACHELINE_LEN,
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]
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}) as Box<dyn Fn(usize, usize) -> Vec<usize>>
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}) as Box<dyn Fn(isize) -> Box<dyn Fn(usize, usize) -> Vec<usize>>>,
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),
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] {
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for k in [4 as isize, 3, 2, 1, -1, -2, -3, -4] {
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experiments.push((format!("{}{}", class.0, k), PAGE_CACHELINE_LEN, PAGE_CACHELINE_LEN, class.1(k)));
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}
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}
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let mut prober = Prober::<1>::new(63).unwrap();
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for experiment in experiments {
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let tag = &experiment.0;
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let mut patterns = vec![];
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for i in 0..experiment.1 {
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for j in 0..experiment.2 {
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patterns.push(experiment.3(i, j))
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}
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}
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let i = patterns[0].len();
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exp(i, tag, &patterns, args.same_ip, args.unique_ip, &mut prober);
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}
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}
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