Miscellaneous¶

Static Intersection Checks¶

Static intersection checks are not a core part of the IPC algorithm, but they are useful for debugging and verifying your input is intersection-free. The IPC Toolkit provides a function for checking if a mesh is intersection-free:

C++ Python

bool is_intersecting = ipc::has_intersections(collision_mesh, displaced);

is_intersecting = ipctk.has_intersections(collision_mesh, displaced)

Logger¶

The IPC Toolkit uses the spdlog library for logging. By default, the IPC Toolkit will log to stdout. To change this behavior, you can set the logger using the ipc::set_logger function. For example, to additionally log to a file, you can do the following:

C++ Python

std::string log_file = "log.txt";

std::vector<spdlog::sink_ptr> sinks;
sinks.emplace_back(std::make_shared<spdlog::sinks::stdout_color_sink_mt>());
sinks.emplace_back(std::make_shared<spdlog::sinks::basic_file_sink_mt>(log_file, /*truncate=*/true));

ipc::set_logger(std::make_shared<spdlog::logger>("ipctk", sinks.begin(), sinks.end()));

# Unfortunately, this is not yet supported in Python.

You can also set the log level:

C++ Python

ipc::logger().set_level(spdlog::level::debug);

ipctk.set_logger_level(ipctk.LoggerLevel.debug)

Multi-threading¶

The IPC Toolkit utilizes oneTBB to enable multi-threading functionality. This is enabled by default, and significantly improves performance. However, with multi-threading enabled, it is expected that the results can be non-deterministic because of rounding differences when adding numbers in different orders. To make the results deterministic you can limit TBB’s maximum number of threads to one. The following code shows how to do this:

C++ Python

#include <tbb/global_control.h>

// ...

tbb::global_control thread_limiter(tbb::global_control::max_allowed_parallelism, 1);

As long as this thread_limiter object stays alive, the number of threads will be limited to 1. This example shows the thread limiter stack allocated, so when the object goes out-of-scope, the limit will be released. If you want this limit for the entire length of your program it is best to define it in main or to define it statically using a std::shared_ptr<tbb::global_control>. For example,

#include <tbb/info.h>
#include <tbb/global_control.h>

static std::shared_ptr<tbb::global_control> thread_limiter;

void set_num_threads(int nthreads)
{
    if (nthreads <= 0) {
        nthreads = tbb::info::default_concurrency();
    } else if (nthreads > tbb::info::default_concurrency()) {
        logger().warn(
            "Attempting to use more threads than available ({:d} > {:d})!",
            nthreads, tbb::info::default_concurrency());
        nthreads = tbb::info::default_concurrency();
    }
    thread_limiter = std::make_shared<tbb::global_control>(
        tbb::global_control::max_allowed_parallelism, nthreads);
}

ipctk.set_num_threads(1)

This limit will persist for the duration of the program or until you call

ipctk.set_num_threads(-1)

to reset the number of threads to the default.

You can also get the current maximum number of threads as follows:

C++ Python

int nthreads = tbb::global_control::active_value(tbb::global_control::max_allowed_parallelism);

Additionally, you can get the number of threads TBB will use by default:

#include <tbb/info.h>

// ...

int max_nthreads = tbb::info::default_concurrency();

nthreads = ipctk.get_num_threads()

Last update: Apr 03, 2024