Python 代码实现高性能异构分布式并行编译系统
任务分解模块（Task Decomposition）
class TaskDecomposer:
def __init__(self, source_code):
self.source_code = source_code
def decompose(self):
# 简单示例：假设代码文件分解成多个独立的文件
files = self.source_code.split('\n\n') # 假设每两个换行符分割一个文件
tasks = [f'task_{i}.c' for i in range(len(files))]
for i, file in enumerate(files):
with open(tasks[i], 'w') as f:
f.write(file)
return tasks
# 示例用法
source_code = "int main() {return 0;}\n\nint add(int a, int b) {return a + b;}"
decomposer = TaskDecomposer(source_code)
tasks = decomposer.decompose()
print(tasks)
任务调度模块（Task Scheduling）
class TaskScheduler:
def __init__(self, tasks, nodes):
self.tasks = tasks
self.nodes = nodes
def schedule(self):
# 简单的轮询调度算法
schedule = {}
for i, task in enumerate(self.tasks):
node = self.nodes[i % len(self.nodes)]
if node not in schedule:
schedule[node] = []
schedule[node].append(task)
return schedule
# 示例用法
nodes = ['node1', 'node2', 'node3']
scheduler = TaskScheduler(tasks, nodes)
schedule = scheduler.schedule()
print(schedule)
编译执行模块（Compilation Execution）
import subprocess
class CompilationExecutor:
def __init__(self, schedule):
self.schedule = schedule
def execute(self):
results = {}
for node, tasks in self.schedule.items():
for task in tasks:
result = self.compile_on_node(node, task)
results[task] = result
return results
def compile_on_node(self, node, task):
# 简单示例：假设本地编译
cmd = f'gcc {task} -o {task.split(".")[0]}'
try:
output = subprocess.check_output(cmd, shell=True, stderr=subprocess.STDOUT)
return output.decode()
except subprocess.CalledProcessError as e:
return e.output.decode()
# 示例用法
executor = CompilationExecutor(schedule)
results = executor.execute()
print(results)
结果合并模块（Result Merging）
class ResultMerger:
def __init__(self, results):
self.results = results
def merge(self):
# 简单示例：将所有编译好的文件链接成一个可执行文件
object_files = [f'{task.split(".")[0]}.o' for task in self.results.keys()]
cmd = f'gcc {" ".join(object_files)} -o final_executable'
try:
output = subprocess.check_output(cmd, shell=True, stderr=subprocess.STDOUT)
return output.decode()
except subprocess.CalledProcessError as e:
return e.output.decode()
# 示例用法
merger = ResultMerger(results)
merge_result = merger.merge()
print(merge_result)
错误处理模块（Error Handling）
class ErrorHandler:
def __init__(self, results):
self.results = results
def handle_errors(self):
errors = {}
for task, result in self.results.items():
if "error" in result:
errors[task] = result
return errors
# 示例用法
error_handler = ErrorHandler(results)
errors = error_handler.handle_errors()
print(errors)
C++ 代码实现高性能异构分布式并行编译系统
任务分解模块（Task Decomposition）
#include <iostream>
#include <fstream>
#include <vector>
#include <sstream>
class TaskDecomposer {
public:
TaskDecomposer(const std::string& source_code) : source_code(source_code) {}
std::vector<std::string> decompose() {
std::vector<std::string> tasks;
std::stringstream ss(source_code);
std::string file_content;
int task_number = 0;
while (std::getline(ss, file_content, '\n\n')) { // 假设每两个换行符分割一个文件
std::string task_filename = "task_" + std::to_string(task_number++) + ".cpp";
std::ofstream outfile(task_filename);
outfile << file_content;
outfile.close();
tasks.push_back(task_filename);
}
return tasks;
}
private:
std::string source_code;
};
int main() {
std::string source_code = "int main() { return 0; }\n\nint add(int a, int b) { return a + b; }";
TaskDecomposer decomposer(source_code);
std::vector<std::string> tasks = decomposer.decompose();
for (const auto& task : tasks) {
std::cout << task << std::endl;
}
return 0;
}
任务调度模块（Task Scheduling）
#include <iostream>
#include <vector>
#include <unordered_map>
class TaskScheduler {
public:
TaskScheduler(const std::vector<std::string>& tasks, const std::vector<std::string>& nodes)
: tasks(tasks), nodes(nodes) {}
std::unordered_map<std::string, std::vector<std::string>> schedule() {
std::unordered_map<std::string, std::vector<std::string>> schedule;
for (size_t i = 0; i < tasks.size(); ++i) {
const auto& node = nodes[i % nodes.size()];
schedule[node].push_back(tasks[i]);
}
return schedule;
}
private:
std::vector<std::string> tasks;
std::vector<std::string> nodes;
};
int main() {
std::vector<std::string> tasks = { "task_0.cpp", "task_1.cpp" };
std::vector<std::string> nodes = { "node1", "node2", "node3" };
TaskScheduler scheduler(tasks, nodes);
auto schedule = scheduler.schedule();
for (const auto& [node, tasks] : schedule) {
std::cout << "Node: " << node << std::endl;
for (const auto& task : tasks) {
std::cout << " Task: " << task << std::endl;
}
}
return 0;
}
编译执行模块（Compilation Execution）
#include <iostream>
#include <vector>
#include <unordered_map>
#include <cstdlib>
class CompilationExecutor {
public:
CompilationExecutor(const std::unordered_map<std::string, std::vector<std::string>>& schedule)
: schedule(schedule) {}
std::unordered_map<std::string, std::string> execute() {
std::unordered_map<std::string, std::string> results;
for (const auto& [node, tasks] : schedule) {
for (const auto& task : tasks) {
std::string result = compileOnNode(node, task);
results[task] = result;
}
}
return results;
}
private:
std::unordered_map<std::string, std::vector<std::string>> schedule;
std::string compileOnNode(const std::string& node, const std::string& task) {
std::string cmd = "g++ " + task + " -o " + task.substr(0, task.find_last_of('.')) + ".o";
std::string result = executeCommand(cmd);
return result;
}
std::string executeCommand(const std::string& cmd) {
char buffer[128];
std::string result;
FILE* pipe = popen(cmd.c_str(), "r");
if (!pipe) throw std::runtime_error("popen() failed!");
try {
while (fgets(buffer, sizeof buffer, pipe) != nullptr) {
result += buffer;
}
} catch (...) {
pclose(pipe);
throw;
}
pclose(pipe);
return result;
}
};
int main() {
std::unordered_map<std::string, std::vector<std::string>> schedule = {
{"node1", {"task_0.cpp"}},
{"node2", {"task_1.cpp"}}
};
CompilationExecutor executor(schedule);
auto results = executor.execute();
for (const auto& [task, result] : results) {
std::cout << "Task: " << task << "\nResult: " << result << std::endl;
}
return 0;
}
结果合并模块（Result Merging）
#include <iostream>
#include <vector>
#include <unordered_map>
#include <cstdlib>
class ResultMerger {
public:
ResultMerger(const std::unordered_map<std::string, std::string>& results)
: results(results) {}
std::string merge() {
std::vector<std::string> object_files;
for (const auto& [task, result] : results) {
if (result.find("error") == std::string::npos) {
object_files.push_back(task.substr(0, task.find_last_of('.')) + ".o");
}
}
std::string cmd = "g++ ";
for (const auto& file : object_files) {
cmd += file + " ";
}
cmd += "-o final_executable";
std::string result = executeCommand(cmd);
return result;
}
private:
std::unordered_map<std::string, std::string> results;
std::string executeCommand(const std::string& cmd) {
char buffer[128];
std::string result;
FILE* pipe = popen(cmd.c_str(), "r");
if (!pipe) throw std::runtime_error("popen() failed!");
try {
while (fgets(buffer, sizeof buffer, pipe) != nullptr) {
result += buffer;
}
} catch (...) {
pclose(pipe);
throw;
}
pclose(pipe);
return result;
}
};
int main() {
std::unordered_map<std::string, std::string> results = {
{"task_0.cpp", "Compilation successful"},
{"task_1.cpp", "Compilation successful"}
};
ResultMerger merger(results);
std::string merge_result = merger.merge();
std::cout << "Merge Result: " << merge_result << std::endl;
return 0;
}
错误处理模块（Error Handling）
#include <iostream>
#include <unordered_map>
class ErrorHandler {
public:
ErrorHandler(const std::unordered_map<std::string, std::string>& results)
: results(results) {}
std::unordered_map<std::string, std::string> handleErrors() {
std::unordered_map<std::string, std::string> errors;
for (const auto& [task, result] : results) {
if (result.find("error") != std::string::npos) {
errors[task] = result;
}
}
return errors;
}
private:
std::unordered_map<std::string, std::string> results;
};
int main() {
std::unordered_map<std::string, std::string> results = {
{"task_0.cpp", "Compilation successful"},
{"task_1.cpp", "Compilation error: undefined reference"}
};
ErrorHandler error_handler(results);
auto errors = error_handler.handleErrors();
for (const auto& [task, error] : errors) {
std::cout << "Task: " << task << "\nError: " << error << std::endl;
}
return 0;
}
通过以上模块的实现，可以构建一个基本的高性能异构分布式并行编译系统。实际应用中可能需要更复杂的任务分解、调度算法、分布式执行环境的配置及优化等。
