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papi_wrap.cpp
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papi_wrap.cpp
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#include <mpi.h>
#include <iostream>
#include <fstream>
#include <cstdlib>
#include <cstring>
#include <cmath>
#include <ctime>
#include <zconf.h>
#include <cstdlib>
#include <cstdio>
#include <climits>
#include <papi.h>
#include <vector>
#include <string>
#include <map>
#include <set>
#include <string>
#include <cassert>
#include <algorithm>
#include <execinfo.h> // gcc-version backtrace
#include <json/json.h>
//#define UNW_LOCAL_ONLY
//#include <libunwind.h> // libunwind-version backtrace
#include "papi_wrap.h"
#include "clustering.h"
#include "utility.h"
#include <linux/perf_event.h>
// gettimeofday
//#include<sys/time.h>
#include <unistd.h>
#include <sstream>
#include <syscall.h>
#include <sys/ioctl.h>
#include "online_analyse.h"
#include "SocketClient.h"
// PMU, rdtsc
#include "pmu.h"
#include "pmc_wrapper.h"
#define likely(x) __builtin_expect(!!(x), 1)
#define unlikely(x) __builtin_expect(!!(x), 0)
using namespace std;
const long long Cpu_freq = CPU_FREQ;
// using DataType=std::vector<long long>;
// using GraphKey=std::pair<void*,void*>;
// using GraphValue=std::vector<DataType >;
int events[6] = {PAPI_TOT_INS, PAPI_L1_TCM, PAPI_L2_TCM, PAPI_BR_MSP, PAPI_VEC_DP}; //, PAPI_SR_INS}; //, PAPI_LD_INS, PAPI_L3_TCA};
const int J_MPI_INIT = 0;
const int J_MPI_BARRIER = 23;
const int J_MPI_WAIT = 317;
const int J_MPI_COMM_RANK = 61;
const int J_MPI_COMM_SIZE = 68;
const int J_MPI_WTIME = 359;
const int J_MPI_WAITANY = 319;
const int J_MPI_WAITALL = 318;
const int J_MPI_FILE_WRITE_AT_ALL = 138;
const int J_MPI_FILE_READ_AT_ALL = 118;
const int J_MPI_ALLREDUCE = 16;
const int J_MPI_FILE_READ_AT = 117;
const int J_MPI_FILE_WRITE_AT = 137;
const int J_MPI_Irecv = 4;
const int J_MPI_Iporbe = 208;
const int J_MPI_Testall = 271;
const int J_DYNINST = 999; // Dyninst instrumentation
const set<int> FILTER_OUT_MPI = {J_MPI_INIT, J_MPI_BARRIER, J_MPI_WAIT,
J_MPI_COMM_RANK, J_MPI_COMM_SIZE, J_MPI_WTIME,
J_MPI_WAITANY, J_MPI_WAITALL, J_MPI_Irecv,
J_MPI_Iporbe, J_MPI_Testall};
// const set<int> FILTER_OUT_MPI = {J_MPI_INIT, J_MPI_BARRIER, J_MPI_WAIT, J_MPI_COMM_RANK, J_MPI_COMM_SIZE, J_MPI_WTIME};
const set<int> IO_MPI = {J_MPI_FILE_READ_AT_ALL, J_MPI_FILE_WRITE_AT_ALL, J_MPI_FILE_READ_AT, J_MPI_FILE_WRITE_AT};
struct SummaryType
{
double total_run_time;
double covered_calc_time, covered_comm_time;
int edge_cnt, vertex_cnt;
/**
*
* @return String of a json with line feed
*/
string generate_summary_json()
{
Json::Value output;
ostringstream os;
output["total_run_time"] = total_run_time;
output["covered_calc_time"] = covered_calc_time;
output["covered_comm_time"] = covered_comm_time;
output["calc_covered_ratio"] = covered_calc_time / total_run_time;
output["comm_covered_ratio"] = covered_comm_time / total_run_time;
output["total_covered_ratio"] = (covered_calc_time + covered_comm_time) / total_run_time;
output["edge_cnt"] = edge_cnt;
output["vertex_cnt"] = vertex_cnt;
Json::FastWriter fast_writer;
os << fast_writer.write(output);
return os.str();
}
} summary;
static void *last_call_addr = nullptr;
int cnt_address;
map<void *, int> address_map;
map<void *, int> address_to_func;
map<void *, DataType> last_data_map;
Graph graph_calc, graph_comm, graph_io;
// counter of clustering result
map<GraphKey, int> cluster_cnt;
bool init_flag = false;
// finish flag is necessary because of the occurrence of hooked function in print_graph
bool finish_flag = false;
// ignore recursively invoked MPI function. For instance, PMPI_File_set_view
// invokes MPI_Type_size_x.
bool in_mpi_flag = false;
int recursive_depth = 0;
// switch for online analysis
constexpr bool online_analyze_flag = false;
// switch for analysis server
constexpr bool online_server_flag = false;
// switch for sampling
//#define ENABLE_SAMPLING
constexpr bool sampling_flag = false;
double sampling_rate = 0.01;
int mpi_rank = -1, mpi_size = -1;
VertexType vertex_type = VertexType::CallSite;
// online anaylsis
Graph graph_last_calc, graph_last_comm, graph_last_io;
int env_vapro_online_period = 5; // unit: second
// server analysis
int env_vapro_server_period = 15; // unit: second
SocketClient *socketClient;
char *server_addr;
int server_port;
unsigned long long init_time;
unsigned long long last_time;
// unsigned long long last_totcycle = 0;
vector<ULL> last_pmcs(CNT_PAPI_EVENTS, 0);
void pmc_enable()
{
init_time = rdtsc();
// wrapper for pmc API
pmc_enable_real();
// get VERTEX_GRAIN
char *vertex_path_str = getenv("VERTEX_GRAIN");
int vertex_path_int = (vertex_path_str == 0) ? VertexType::CallSite : atoi(vertex_path_str);
assert(!(vertex_path_int < 0 || vertex_path_int > 2));
if (vertex_path_int < 0 || vertex_path_int > 2)
{
fprintf(stderr, "vertex path environment variable error");
exit(-1);
}
else
vertex_type = (VertexType)vertex_path_int;
init_flag = true;
}
/**
* This function has side effect. It changes last_time and last_totcycle.
* @param cur_time
* @return
*/
inline DataType pmc_get_data(ULL cur_time)
{
auto new_pmcs = pmc_read_real();
ULL diff_pmcs[CNT_PAPI_EVENTS];
for (int i = 0; i < CNT_PAPI_EVENTS; ++i)
diff_pmcs[i] = new_pmcs[i] - last_pmcs[i];
DataType retv;
retv.set_papi_data(diff_pmcs);
retv.elapsed = cur_time - last_time; // append wall time to locate this record
retv.timestamp = cur_time;
last_time = cur_time;
last_pmcs = std::move(new_pmcs);
return retv;
}
void vapro_init()
{
PMPI_Comm_rank(MPI_COMM_WORLD, &mpi_rank);
PMPI_Comm_size(MPI_COMM_WORLD, &mpi_size);
// DEBUG
// char *env_vapro_online_period = getenv("VAPRO_ONLINE_PERIOD");
if (mpi_rank == 0)
{
fprintf(stderr, "Shared library loaded..\n");
fprintf(stderr, "INFO: vertex_path_int = %d\n", vertex_type);
}
if (online_analyze_flag)
{
if (mpi_rank == 0)
fprintf(stderr, "INFO: online mode ON. period=%d\n", env_vapro_online_period);
online_anaylze_init();
}
else if (online_server_flag)
{
server_addr = getenv("VAPRO_SERVER_IP");
if (!server_addr)
{
fprintf(stderr, "VAPRO_SERVER_IP is not defined.\n");
exit(-1);
}
const char *vapro_server_port = getenv("VAPRO_SERVER_PORT");
if (!vapro_server_port)
{
fprintf(stderr, "VAPRO_SERVER_PORT is not defined.\n");
exit(-1);
}
server_port = atoi(vapro_server_port);
if (mpi_rank == 0)
{
fprintf(stderr, "INFO: online server ON. period=%d. Server=%s:%d\n",
env_vapro_server_period, server_addr, server_port);
}
socketClient = new SocketClient(server_addr, server_port);
}
else
{
if (mpi_rank == 0)
fprintf(stderr, "INFO: online mode OFF.\n");
}
}
void insert_data(map<GraphKey, GraphValue> &graph, void *last_addr, void *current_addr, DataType &papi_data)
{
if (!address_map.count(current_addr))
{
address_map[current_addr] = cnt_address++;
address_to_func[current_addr] = papi_data.mpi_func;
}
if (!address_map.count(last_addr))
{
address_map[last_addr] = cnt_address++;
}
auto key = make_pair(last_addr, current_addr);
if (!graph.count(key))
graph[key] = GraphValue();
graph[key].push_back(papi_data);
// // differentiate to calculate self loop data
// for (int i = 0; i < CNT_PAPI_EVENTS+1; ++i)
// {
// accumulate_data[i] += papi_data[i];
// }
//
// // insert self loop value
// if (last_addr != current_addr && last_data_map.count(current_addr))
// {
// DataType self_loop_data{accumulate_data};
// for (int i = 0; i < CNT_PAPI_EVENTS+1; ++i)
// self_loop_data[i] -= last_data_map[current_addr][i];
// key = make_pair(current_addr, current_addr);
// if (!graph.count(key))
// graph[key] = GraphValue();
// self_loop_data.insert(self_loop_data.end(), mpi_data.begin(), mpi_data.end());
// if (self_loop_data.size()<all_data.size())
// self_loop_data.resize(all_data.size());
// graph[key].push_back(self_loop_data);
// }
//
// // update last call data for the current call point
// last_data_map[current_addr] = accumulate_data;
}
void *backtrace_buffer[10];
int trace_size;
void output_backtrace()
{
puts("=====");
backtrace_symbols_fd(backtrace_buffer, trace_size, 1);
}
__attribute_noinline__ void *get_invoke_point()
{
// This compiler function(MACRO?) have some strange problems
// return __builtin_return_address(2);
// constexpr int size = 5;
// todo: revert
static bool a = vertex_type == VertexType::CallSite;
// static int cnt=0; //Debug
if (likely(a))
// if (false)
{
// Upd1: UNROLL the loop. Loop may introduce 50% overhead. Unrolling can reduce it to 10%.
// // Irregualr stack
// for (int i = 1; i < trace_size; ++i)
// if (((unsigned long long)backtrace_buffer[i]) < 0x1d627d61)
// return backtrace_buffer[i];
return backtrace_buffer[1]; // for HPL and other apps
// return backtrace_buffer[2]; // for AMG
}
else if (vertex_type == VertexType::CallPath)
{
return (void *)hash_sequence(trace_size, backtrace_buffer);
}
// printf("==ERROR===\n");
// for (int j = 0; j < trace_size; ++j)
// {
// printf("d%d=%lx ch=%d\n", j, (unsigned long) buffer[j],
// ((unsigned long long) buffer[j] < 0x00645cbdeb8eLL));
// }
// printf("=====\n");
output_backtrace();
fprintf(stderr, "Error: Backtrace do not find EXE SEG call stack\n");
assert(0);
exit(1);
}
/**
* @param suffix should be 0 or 1. 0 is before MPI invocation and 1 is after.
*/
__attribute_noinline__ void papi_update(int suffix, int mpi_func, int count, int target, void *mpi_comm)
{
if (!init_flag)
{
// #ifdef USE_PAPI
// papi_init();
// #else
pmc_enable();
// #endif
// fprintf(stderr, "INFO: start online init, rank=%d\n", mpi_rank);
int inited = 0;
MPI_Initialized(&inited);
// if (inited && suffix==0)
// The wrapper of MPI_Init has only suffix 1
if (inited)
vapro_init();
else
return;
if (mpi_rank == 0)
fprintf(stderr, "INFO: Vapro init, rank=%d\n", mpi_rank);
}
// if finished
if (finish_flag)
return;
// Get PMU data ASAP to exclude Vapro noise
unsigned long long current_tsc = rdtsc();
auto papi_data = pmc_get_data(current_tsc);
#ifdef USE_RUSAGE
papi_data.set_rusage_data(get_rusage_data().data());
#endif
papi_data.mpi_func = mpi_func;
papi_data.mpi_count = count;
papi_data.target = target;
papi_data.mpi_comm = mpi_comm;
// skip in recursive mpi invocations
// There might be recursive in MPI libraries.
if (in_mpi_flag && suffix == 0)
{
recursive_depth++;
return;
}
if (recursive_depth > 0 && suffix == 1)
{
recursive_depth--;
return;
}
in_mpi_flag = (suffix == 0);
// online analysis
static unsigned long long last_online_tsc = current_tsc;
static int num_iters = 0;
if (online_analyze_flag && init_flag)
{
if (current_tsc > last_online_tsc +
(unsigned long)(env_vapro_online_period * CPU_FREQ))
{
if (num_iters)
{
online_analyze(current_tsc, last_online_tsc);
}
online_irecv_all();
online_isend_all(graph_calc, graph_comm, graph_io, last_online_tsc,
current_tsc);
graph_last_calc = std::move(graph_calc);
graph_last_comm = std::move(graph_comm);
graph_last_io = std::move(graph_io);
graph_calc.clear();
graph_comm.clear();
graph_io.clear();
last_online_tsc = current_tsc;
++num_iters;
}
}
// server analysis
if (online_server_flag && init_flag)
{
if (current_tsc > last_online_tsc +
(unsigned long)(env_vapro_server_period * CPU_FREQ))
{
socketClient->serialize(mpi_rank, last_online_tsc - init_time,
current_tsc - init_time, graph_calc,
graph_comm, graph_io);
graph_calc.clear();
graph_comm.clear();
graph_io.clear();
socketClient->send();
last_online_tsc = current_tsc;
}
}
long long real_addr;
if (suffix == 1 && last_call_addr)
{
real_addr = (long long)last_call_addr;
}
else
{
if (mpi_func == J_DYNINST)
real_addr = -target;
else
real_addr = (vertex_type == VertexType::Function) ? mpi_func : (long long)get_invoke_point();
}
void *current_call_addr = (void *)(real_addr);
#ifdef ENABLE_SAMPLING
if (sampling_flag && (double(rand_longlong()) > sampling_rate * ULLONG_MAX))
#endif
if (!(suffix == 1 && FILTER_OUT_MPI.count(mpi_func)))
{
if (suffix == 0)
{
if (!(last_call_addr == current_call_addr &&
FILTER_OUT_MPI.count(mpi_func)))
{
insert_data(graph_calc, last_call_addr, current_call_addr,
papi_data);
}
}
else
{
if ((IO_MPI.count(mpi_func)))
{
insert_data(graph_io,
last_call_addr, current_call_addr, papi_data);
}
else
{
// TODO: collective online
insert_data(graph_comm,
last_call_addr, current_call_addr, papi_data);
}
}
}
last_call_addr = current_call_addr;
// reset base counter
last_time = rdtsc();
// #ifdef USE_PAPI
// papi_get_data(last_time); // reset PAPI counter
// #else
// last_totcycle = rdpmc_instructions();
// #ifndef USE_ASSEMBLY_RDPMC
// pmc_reset();
// #endif
// #endif
last_pmcs = pmc_read_real();
last_time = rdtsc();
}
void *get_addr_from_mixture(void *p)
{
return (void *)(((long)p) >> 1);
}
int get_status_from_mixture(void *p)
{
return (int)(((long)p) & 1);
}
struct Interval
{
double l, r;
double perf;
};
typedef vector<Interval> PathPerformance;
/**
* Calculate relative performance from snippets records
* @param path_data
* @param smooth: enable smoothing or not
* @return
*/
PathPerformance calc_path(GraphValue &path_data, bool smooth)
{
unsigned long long min_elapsed = ULONG_LONG_MAX;
PathPerformance ret;
Interval interval;
const int window = 16; // window size of smoothing
vector<ULL> smoothed;
ULL sum = 0;
// if size is enough, smooth the results
if (path_data.size() > window && smooth)
{
for (int i = 0; i < window; ++i)
{
sum += path_data[i].elapsed;
}
smoothed.push_back(sum);
for (auto i = window; i < path_data.size(); ++i)
{
sum += path_data[i].elapsed - path_data[i - window].elapsed;
smoothed.push_back(sum);
}
for (auto &v : smoothed)
min_elapsed = min(v, min_elapsed);
for (int i = 0; i < path_data.size() - window; ++i)
{
const auto &value = path_data[i];
interval.perf = min_elapsed / double(smoothed[i]);
interval.l = double(value.timestamp - value.elapsed - init_time) /
CPU_FREQ;
interval.r = double(value.timestamp - init_time) / CPU_FREQ;
ret.push_back(interval);
}
}
else
{
for (const auto &value : path_data)
min_elapsed = (min_elapsed <= value.elapsed) ? min_elapsed : value.elapsed;
for (const auto &value : path_data)
{
interval.perf = min_elapsed / double(value.elapsed);
interval.l = double(value.timestamp - value.elapsed - init_time) / CPU_FREQ;
interval.r = double(value.timestamp - init_time) / CPU_FREQ;
// // debug
// if (interval.l<1&& interval.r>1)
// {
// for (auto t:path_data)
// printf("Warn: %d %d %lf %lf %d %d\n", t.mpi_func, t.mpi_count, interval.l, interval.r, t.src, t.dst);
// }
ret.push_back(interval);
}
}
return ret;
}
bool online_is_same_calc_cluster(double mean_cycles, double remote_mean_cycles)
{
return (1 - 0.02) * mean_cycles < remote_mean_cycles &&
remote_mean_cycles < (1 + 0.02) * mean_cycles;
}
bool online_is_same_comm_cluster(double mpi_count, double remote_mpi_count)
{
return fabs(remote_mpi_count - mpi_count) < eps;
}
PathPerformance online_calc_path(bool is_calc, GraphValue &path_data,
vector<pair<double, double>> &interprocess_min_time,
bool enable_output = false)
{
unsigned long long min_elapsed = LONG_LONG_MAX;
PathPerformance ret;
Interval interval;
double mean_cycles = 0;
int cnt_interprocess_make_effective = 0; // debug
for (const auto &value : path_data)
{
min_elapsed = (min_elapsed <= value.elapsed) ? min_elapsed
: value.elapsed;
mean_cycles += value.papi[I_PAPI_TOT_INS];
}
assert(path_data.size());
mean_cycles /= path_data.size();
ULL local_min_elapsed = min_elapsed;
// // debug
// if (mpi_rank == 1)
// {
// fprintf(stderr, "local path_mean=%.3lf min_time=%.3lf\n", mean_cycles,
// min_elapsed / CPU_FREQ);
// for (auto &tt:interprocess_min_time)
// {
// fprintf(stderr, "gloabl mean=%.3lf min_time=%.3lf\n", tt.first, tt.second);
// }
// }
for (const auto &record : interprocess_min_time)
{
if ((is_calc &&
online_is_same_calc_cluster(mean_cycles, record.first)) ||
(!is_calc &&
online_is_same_comm_cluster(path_data[0].mpi_count, record.first)))
{
if (min_elapsed > (unsigned long long)(record.second * CPU_FREQ))
{
++cnt_interprocess_make_effective;
min_elapsed = (unsigned long long)(record.second * CPU_FREQ);
}
}
}
// debug
if (mpi_rank == 0 && enable_output)
fprintf(stderr,
"DEBUG: among %lu cnt_interprocess_make_effective=%d lt=%llu gt=%llu\n",
interprocess_min_time.size(), cnt_interprocess_make_effective,
local_min_elapsed, min_elapsed);
for (const auto &value : path_data)
{
interval.perf = min_elapsed / double(value.elapsed);
interval.l =
double(value.timestamp - value.elapsed - init_time) / CPU_FREQ;
interval.r = double(value.timestamp - init_time) / CPU_FREQ;
// // debug
// if (interval.l<1&& interval.r>1)
// {
// for (auto t:path_data)
// printf("Warn: %d %d %lf %lf %d %d\n", t.mpi_func, t.mpi_count, interval.l, interval.r, t.src, t.dst);
// }
ret.push_back(interval);
}
return ret;
}
bool path_data_adequate(const GraphValue &path_data)
{
return path_data.size() >= 5;
}
bool path_stable(const GraphValue &path_data)
{
const double variance = 0.04;
long long inst_min = LONG_LONG_MAX, inst_max = 0;
for_each(path_data.begin(), path_data.end(),
[&inst_min, &inst_max](const DataType &data)
{
inst_min = min(inst_min, data.papi[I_PAPI_TOT_INS]);
inst_max = max(inst_max, data.papi[I_PAPI_TOT_INS]);
});
return (inst_max - inst_min) / (double(inst_max + inst_min) / 2) < variance;
}
vector<double> merge_interval_arithmetic_mean(vector<Interval> &intervals, int l, int r)
{
sort(intervals.begin(), intervals.end(), [](Interval a, Interval b)
{ return a.l < b.l; });
// debug
// printf("intervals len=%lu\n", intervals.size());
// for_each(intervals.begin(), intervals.end(), [](Interval interval) {
// printf("%lf %lf %lf\n", interval.l, interval.r, interval.perf);
// });
double sum = 0;
int cnt = 0;
auto rit = intervals.cbegin();
vector<double> ret;
vector<int> rank_r;
int lit = 0;
for (int i = 0; i < intervals.size(); ++i)
rank_r.push_back(i);
sort(ret.begin(), ret.end(), [&intervals](int a, int b)
{ return intervals[a].r < intervals[b].r; });
for (int i = l; i < r; ++i)
{
// // debug
// printf("=================i=%d========\n", i);
// rit is iterator of the interval whose l is the largest
while (rit != intervals.cend() && rit->l <= i + 1)
{
++cnt;
sum += rit->perf;
if (i == 0)
printf("+ %lf %lf\n", rit->l, rit->r);
++rit;
}
while (intervals[rank_r[lit]].r < i)
{
--cnt;
sum -= intervals[rank_r[lit]].perf;
if (i == 1)
printf("- %lf %lf\n", intervals[rank_r[lit]].l, intervals[rank_r[lit]].r);
++lit;
}
printf("i=%2d cnt=%d\n", i, cnt);
if (cnt)
ret.push_back(sum / cnt);
else // -1 means this interval is not covered
ret.push_back(-0.00001);
}
return ret;
}
vector<double> merge_interval_weighted_mean(vector<Interval> &intervals, int l, int r, double step = 1)
{
sort(intervals.begin(), intervals.end(), [](Interval a, Interval b)
{ return a.l < b.l; });
// // debug
// if (mpi_rank == 1)
// {
// printf("l=%d r=%d\n", l, r);
// printf("intervals len=%lu\n", intervals.size());
// for_each(intervals.begin(), intervals.end(), [](Interval interval) {
// printf("%lf %lf %lf\n", interval.l, interval.r, interval.perf);
// });
// }
double sum = 0, partial_sum = 0, partial_cnt = 0;
int cnt = 0;
auto rit = intervals.cbegin();
vector<double> ret;
vector<int> rank_r;
int lit = 0;
for (int i = 0; i < intervals.size(); ++i)
rank_r.push_back(i);
sort(ret.begin(), ret.end(), [&intervals](int a, int b)
{ return intervals[a].r < intervals[b].r; });
for (double i = l; i < r; i += step)
{
// // debug
// printf("=================i=%d========\n", i);
partial_cnt = partial_sum = 0;
// rit is iterator of the interval whose l is the largest
while (rit != intervals.cend() && rit->l <= i + step)
{
++cnt;
sum += rit->perf;
partial_sum -= rit->perf * (rit->l - i);
partial_cnt -= (rit->l - i);
// if (i == 0)
// printf("+ %lf %lf\n", rit->l, rit->r);
++rit;
}
while (lit < intervals.size() && intervals[rank_r[lit]].r < i + step)
{
--cnt;
sum -= intervals[rank_r[lit]].perf;
partial_sum += intervals[rank_r[lit]].perf * (intervals[rank_r[lit]].r - i);
partial_cnt += (intervals[rank_r[lit]].r - i);
// if (i == 1)
// printf("- %lf %lf\n", intervals[rank_r[lit]].l, intervals[rank_r[lit]].r);
++lit;
}
// printf("i=%2d cnt=%d\n", i, cnt);
if (fabs(cnt * step + partial_cnt) >= eps)
{
ret.push_back((sum * step + partial_sum) / (cnt * step + partial_cnt));
}
else
{ // -1 means this interval is not covered
ret.push_back(-0.005);
}
}
return ret;
}
/**
* Snippet graph to time-based process relative performance
* @param graph
* @param time_l
* @param time_r
* @return
*/
vector<double> calc_performance_process(Graph &graph, int time_l, int time_r)
{
vector<Interval> all_intervals;
vector<pair<double, double>> *interprocess_min_time = nullptr;
for (auto &kv : graph)
{
vector<vector<DataType>> classified = calc_classify(kv.second, 0.02);
int cnt_stable = 0, cnt_total = 0;
// vector<vector<DataType>> classified = calc_classify_fake(kv.second, 0.02);
if (online_analyze_flag && interprocess_info.count(kv.first))
interprocess_min_time = &interprocess_info[kv.first];
else
interprocess_min_time = nullptr;
for (auto &v : classified)
{
if (path_data_adequate(v) && path_stable(v))
{
cnt_stable++;
PathPerformance new_intervals;
if (interprocess_min_time)
new_intervals = online_calc_path(true, v, *interprocess_min_time);
else
new_intervals = calc_path(v, false);
// statistical data
for (auto &vv : new_intervals)
{
summary.covered_calc_time += vv.r - vv.l;
}
all_intervals.insert(all_intervals.end(), new_intervals.begin(), new_intervals.end());
}
cnt_total++;
}
// to output clustering counter
cluster_cnt[kv.first] = cnt_stable;
}
// printf("all_interval.size=%lu stable=%d total=%d\n", all_intervals.size(), cnt_stable, cnt_total);
auto ret = merge_interval_weighted_mean(all_intervals, time_l, time_r);
return ret;
}
Json::Value commbreakdownOutput;
void dump_addr_interval_map(
const std::map<pair<void *, void *>, vector<PathPerformance>> &data)
{
Json::Value output;
for (const auto &kv : data)
{
Json::Value key;
Json::Value value;
key.append((Json::UInt64)kv.first.first);
key.append((Json::UInt64)kv.first.second);
for (const auto &v : kv.second)
{
Json::Value pathPerformance;
for (auto vv : v)
{
Json::Value interval;
interval.append(vv.l);
interval.append(vv.r);
interval.append(vv.perf);
pathPerformance.append(interval);
}
value.append(pathPerformance);
}
output.append(key);
output.append(value);
}
commbreakdownOutput.append(output);
}
/**
* Output commbreakdownOutput to file
* @param filename_prefix
*/
void dump_addr_interval_map_to_file(string filename_prefix)
{
string filename = filename_prefix + std::to_string((long long)mpi_rank) +
string(".txt");
ofstream os;
os.open(filename.c_str());
Json::FastWriter fast_writer;
os << fast_writer.write(commbreakdownOutput);
commbreakdownOutput.clear();
os.close();
}
vector<double> comm_performance_process(Graph &graph, int time_l, int time_r,
bool enable_output = false)
{
vector<Interval> all_intervals;
vector<pair<double, double>> *interprocess_min_time = nullptr;
std::map<pair<void *, void *>, vector<PathPerformance>> debug_data;
for (auto &kv : graph)
{
vector<vector<DataType>> classified = comm_classify(kv.second);
// vector<vector<DataType>> classified = comm_classify_fake(kv.second);
unsigned long newlen = 0;
int cnt_stable = 0, cnt_total = 0;
debug_data[kv.first] = vector<PathPerformance>();
if (online_analyze_flag && interprocess_info.count(kv.first))
interprocess_min_time = &interprocess_info[kv.first];
else
interprocess_min_time = nullptr;
// debug
if (mpi_rank == 0 && enable_output)
{
printf("IO %lu classes, total interprocess size=%lu, this snippet %lu, key=%p,%p\n",
classified.size(),
interprocess_info.size(),
interprocess_min_time ? interprocess_min_time->size() : -1,
kv.first.first, kv.first.second);
}
for (auto &v : classified)
{
if (mpi_rank == 0 && enable_output)
{
printf("IO class has %lu eles\n", v.size());
}
if (path_data_adequate(v))
{
// debug: print timing to be calced in python
// if (mpi_rank==0) print_timing_for_python(v);
cnt_stable++;
PathPerformance new_intervals;
if (interprocess_min_time)
new_intervals = online_calc_path(false, v, *interprocess_min_time,
enable_output);
else
new_intervals = calc_path(v, true);
// statistical data
for (auto &vv : new_intervals)
{
summary.covered_comm_time += vv.r - vv.l;
newlen++;
}
all_intervals.insert(all_intervals.end(), new_intervals.begin(),
new_intervals.end());
// TODO: DEBUG dump {kv:interval}
debug_data[kv.first].push_back(new_intervals);
// printf("BD: %d")
}
cnt_total++;
}
assert(kv.second.size() >= newlen);
cluster_cnt[kv.first] = cnt_stable;
}
auto ret = merge_interval_weighted_mean(all_intervals, time_l, time_r);
return ret;
}
void print_graph_json(const Graph &graph, int rank, const string &filename_prefix)
{
// debug
double sum_comm_time = 0;
finish_flag = true;
Json::Value output;
string filename = filename_prefix + std::to_string((long long)rank) + string(".txt");
ofstream os;
os.open(filename.c_str());
for (const auto &item : graph)
{
Json::Value list;
// cout << get_addr_from_mixture(item.first.first) << " " <<
// get_status_from_mixture(item.first.first) << " " <<
// get_addr_from_mixture(item.first.second) << " " <<
// get_status_from_mixture(item.first.second) << " " <<
list["info"].append((Json::UInt64)item.first.first);
list["info"].append((Json::UInt64)item.first.second);
// number of clusters with corresponding snippet
list["ccnt"] = cluster_cnt[item.first];
vector<uint64_t> temp_sum(6, 0);
for (const auto &data : item.second)
{
// for (auto value:data)
// one_call.append((uint64_t)value);
Json::Value one_call;
// only place TOT_INST at the beginning
one_call.append((Json::UInt64)data.papi[0]);
one_call.append(data.mpi_func);
one_call.append(data.mpi_count);
one_call.append(data.target);
// debug
one_call.append("T");
one_call.append(double(data.timestamp - init_time) / CPU_FREQ);
if (data.mpi_func == J_MPI_INIT)
one_call.append(-0.00001);
else
{
one_call.append(double(data.elapsed) / CPU_FREQ);
sum_comm_time += double(data.elapsed) / CPU_FREQ;
}
// append other PMU data to the end
for (int i = 1; i < CNT_TOTAL_EVENTS; ++i)
one_call.append((Json::UInt64)data.papi[i]);
list["value"].append(one_call);
}
output["edge"].append(list);
}
Json::FastWriter fast_writer;
os << fast_writer.write(output);
os.close();
}
void print_function_cnt_to_file(FILE *f)
{
map<void *, int> cnt_map;
for (auto kv : graph_comm)
{
// CallPath address(hash value) must be different
if (vertex_type != VertexType::CallPath &&
!(kv.first.first == 0 ||
((long long)kv.first.first) == ((long long)kv.first.second)))
{