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procinproc.github.io's Introduction

Process-in-Process (PiP)

PiP is a user-level library to have the best of the both worlds of multi-process and multi-thread parallel execution models. PiP allows a process to create sub-processes into the same virtual address space where the parent process runs. The parent process and sub-processes share the same address space, however, each process has its own variable set. So, each process runs independently from the other process. If some or all processes agree, then data owned by a process can be accessed by the other processes. Those processes share the same address space, just like pthreads, but each process has its own variables like the process execution model. Hereinafter, the parent process is called PiP process and sub-processes are called PiP tasks.

PiP Versions

Currently there are three PiP library versions:

  • Version 1 - Deprecated
  • Version 2 - Stable version
  • Version 3 - Stable version supporting BLT and ULP (experimental)

Unfortunately each version has unique ABI and there is no ABI compatibility among them. The functionality of PiP-v1 is almost the same with PiP-v2, however, PiP-v2's API is a subset of the PiP-v3's API. Hereafter NN denotes the PiP version number.

Bi-Level Thread (BLT, from v3)

PiP also provides new thread implementation named "Bi-Level Thread (BLT)", again, to take the best of two worlds, Kernel-Level Thread (KLT) and User-Level Thread (ULT) here. A BLT is a PiP task. When a PiP task is created it runs as a KLT. At any point the KLT can become a ULT by decoupling the associated kernel thread from the KLT. The decoupled kernel thread becomes idle. Later, the ULT can become KLT again by coupling with the kernel thread.

User-Level Process (ULP, from v3)

As described, PiP allows PiP tasks to share the same virtual address space. This mans that a PiP task can context-switch to the other PiP task at user-level. This is called User-Level Process where processes may be derived from the same program or different programs. Threads basically share most of the kernel resources, such as address space, file descriptors, a process id, and so on whilst processes do not. Every process has its own file descriptor space, for example. When a ULP is scheduled by a KLT having PID 1000, then the getpid() is called by the ULP returns 1000. Further, when the ULT is migrated to be scheduled by the other KLT, then the returned PID is different. So, when implementing a ULP system, this systemcall consistency must be preserved. In ULP on PiP, the consistency can be maintained by utilizing the above BLT mechanism. When a ULT tries to call a system call, it is coupled with its kernel thread which was created at the beginning as a KLT. It should be note that Thread Local Storage (TLS) regions are also switched when switching ULP (and BLT) contexts.

Execution Mode

There are several PiP implementation modes which can be selected at the runtime. These implementations can be categorized into two;

  • Process and
  • (P)Thread.

In the pthread mode, although each PiP task has its own static variables unlike thread, PiP task behaves more like PThread, having a TID, having the same file descriptor space, having the same signal delivery semantics as Pthread does, and so on. In the process mode, a PiP task behaves more like a process, having a PID, having an independent file descriptor space, having the same signal delivery semantics as Linux process does, and so on. The above mentioned ULP can only work with the process mode.

When the PIP_MODE environment variable set to "thread" then the PiP library runs in the pthread mode, and if it is set to "process" then it runs in the process mode.

Several function are made available by the PiP library to absorb the functional differences due to the execution modes.

License

This package is licensed under the 2-clause simplified BSD License - see the LICENSE file for details.

Installation

Basically PiP requires the following three software packages;

  • PiP - Process in Process (this package)
  • PiP-Testsuite - Testsuite for PiP
  • PiP-glibc - patched GNU libc for PiP
  • PiP-gdb - patched gdb to debug PiP root and PiP tasks.

By using PiP-glibc, users can create up to 300 PiP tasks which can be debugged by using PiP-gdb. In other words, without installing PiP-glibc, users can create up to around 10 PiP tasks (the number depends on the program) and cannot debug by using PiP-gdb.

There are several ways to install the PiP packages; Docker, Spack, and building from the source code. It is strongly recommended to use the following PiP package installation program (pip-pip):

  • PiP-pip - PiP package installing program

This is the easiest way to install PiP packages in any form. Here is the example of pip-pip usage:

$ git clone https://github.com/procinproc/PiP-pip.git
$ cd PiP-pip
$ ./pip-pip --how=HOW --pip=PIP_VERSION --work=BUILD_DIR --prefix=INSTALL_DIR

HOW can be one of docker, spack and github, or any combination of them. pip-pip --help will show you how to use the program. The docker and spack installations include all three packages; PiP, PiP-glibc and PiP-gdb.

PiP Documents

Tutorial

Tutorial PDF

Man pages

Man pages will be installed at PIP_INSTALL_DIR/share/man.

$ man -M PIP_INSTALL_DIR/share/man 7 libpip

Or, use the pip-man command (from v2).

$ PIP_INSTALL_DIR/bin/pip-man 7 libpip

The above two examples will show you the same document you are reading.

PDF

PDF documents will be installed at PIP_INSTALL_DIR/share/doc/PiP/libpip-manpages.pdf.

HTML

HTML documents will be installed at PIP_INSTALL_DIR/share/doc/PiP/index.html.

Getting Started

Compile and link your PiP programs

  • pipcc(1) command (since v2)

You can use pipcc(1) command to compile and link your PiP programs.

$ pipcc -Wall -O2 -g -c pip-prog.c
$ pipcc -Wall -O2 -g pip-prog.c -o pip-prog 

Run your PiP programs

  • pip-exec(1) command (piprun(1) in PiP v1)

Let's assume that you have a non-PiP program(s) and want to run as PiP tasks. All you have to do is to compile your program by using the above pipcc(1) command and to use the pip-exec(1) command to run your program as PiP tasks.

$ pipcc myprog.c -o myprog
$ pip-exec -n 8 ./myprog
$ ./myprog

In this case, the pip-exec(1) command becomes the PiP root and your program runs as 8 PiP tasks. Note that the 'myprog.c' may or may not call any PiP functions. Your program can also run as a normal program (not as a PiP task) without using the pip-exec(1) command. In either case, your programs must be compiled and linked by using the pipcc(1) command described above.

You may write your own PiP programs which includes the PiP root programming. In this case, your program can run without using the pip-exec(1) command.

If you get the following message when you try to run your program;

PiP-ERR(19673) './myprog' is not PIE

Then this means that the 'myprog' (having PID 19673) is not compiled by using the pipcc(1) command properly. You may check if your program(s) can run as a PiP root and/or PiP task by using the pip-check(1) command (from v2);

$ pip-check a.out
a.out : Root&Task

Above example shows that the 'a.out' program can run as a PiP root and PiP tasks.

  • pips(1) command (from v2)

    Similar to the Linux ps command, you can see how your PiP program(s) is (are) running by using the pips(1) command. pips can accept 'a', 'u' and 'x' options just like the ps command.

    $ pips [a][u][x] [PIPS-OPTIONS] [-] [PATTERN ..]

    List the PiP tasks via the 'ps' command;

    $ pips --ps [ PATTERN .. ]

    or, show the activities of PiP tasks via the 'top' command;

    $ pips --top [ PATTERN .. ]

    Additionally you can kill all of your PiP tasks by using the same pips(1) command;

    $ pips -s KILL [ PATTERN .. ]

Debugging your PiP programs by the pip-gdb command

The following procedure is to attach all PiP tasks and PiP root which created those tasks. Each PiP task is treated as a GDB inferior in PiP-gdb. Note that PiP-glibc and PiP-gdb packages are required to do this. Note that all features in this section are only supported by PiP v2 or higher, only with the process execution mode (thread mode and ULP/BLT in PiP v3 are NOT supported).

$ pip-gdb
(pip-gdb) attach PID

The attached inferiors can be seen by the following GDB command:

(pip-gdb) info inferiors
  Num  Description              Executable
  4    process 6453 (pip 2)     /somewhere/pip-task-2
  3    process 6452 (pip 1)     /somewhere/pip-task-1
  2    process 6451 (pip 0)     /somewhere/pip-task-0
* 1    process 6450 (pip root)  /somewhere/pip-root

You can select and debug an inferior by the following GDB command:

(pip-gdb) inferior 2
[Switching to inferior 2 [process 6451 (pip 0)] (/somewhere/pip-task-0)]

When an already-attached program calls 'pip_spawn()' and becomes a PiP root task, the newly created PiP child tasks aren't attached automatically, but you can add empty inferiors and then attach the PiP child tasks to the inferiors. e.g.

.... type Control-Z to stop the root task.
^Z
Program received signal SIGTSTP, Stopped (user).

(pip-gdb) add-inferior
Added inferior 2
(pip-gdb) inferior 2
(pip-gdb) attach 1902

(pip-gdb) add-inferior
Added inferior 3
(pip-gdb) inferior 3
(pip-gdb) attach 1903

(pip-gdb) add-inferior
Added inferior 4
(pip-gdb) inferior 4
(pip-gdb) attach 1904

(pip-gdb) info inferiors
  Num  Description              Executable
* 4    process 1904 (pip 2)     /somewhere/pip-task-2
  3    process 1903 (pip 1)     /somewhere/pip-task-1
  2    process 1902 (pip 0)     /somewhere/pip-task-0
  1    process 1897 (pip root)  /somewhere/pip-root

You can attach all relevant PiP tasks by:

$ pip-gdb -p PID-of-your-PiP-program

(from v2)

If the PIP_GDB_PATH environment is set to the path pointing to PiP-gdb executable file, then PiP-gdb is automatically attached when an exception signal (SIGSEGV or SIGHUP by default) is delivered. The exception signals can also be defined by setting the PIP_GDB_SIGNALS environment. Signal names (case insensitive) can be concatenated by the '+' or '-' symbol. 'all' is reserved to specify most of the signals. For example, 'ALL-TERM' means all signals excepting SIGTERM, another example, 'PIPE+INT' means SIGPIPE and SIGINT. If one of the specified or default signals is delivered, then PiP-gdb will be attached automatically. The PiP-gdb will show backtrace by default. If users specify PIP_GDB_COMMAND, a filename containing some GDB commands, then those GDB commands will be executed by PiP-gdb in batch mode.

If the PIP_STOP_ON_START environment is set, then the PiP library delivers SIGSTOP to a spawned PiP task which is about to start user program. If its value is a number in decimal, then the PiP task whose PiP-ID is the same with the specified number will be stopped. If the number is minus, then all PiP tasks will be stopped at the very beginning. Do not forget to compile your programs with a debug option.

Mailing Lists

If you have any questions or comments on PiP, send e-mails to;

Or, join our PiP users' mailing list;

Publications

Research papers

Atsushi Hori, Min Si, Balazs Gerofi, Masamichi Takagi, Jay Dayal, Pavan Balaji, and Yutaka Ishikawa. "Process-in-process: techniques for practical address-space sharing," In Proceedings of the 27th International Symposium on High-Performance Parallel and Distributed Computing (HPDC '18). ACM, New York, NY, USA, 131-143. DOI: https://doi.org/10.1145/3208040.3208045

Atsushi Hori, Balazs Gerofi, and Yuataka Ishikawa. "An Implementation of User-Level Processes using Address Space Sharing," 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), New Orleans, LA, USA, 2020, pp. 976-984, DOI: https://doi.org/10.1109/IPDPSW50202.2020.00161.

Kaiming Ouyang, Min Si, Atsushi Hori, Zizhong Chen, and Pavan Balaji. 2020. "CAB-MPI: exploring interprocess work-stealing towards balanced MPI communication," In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '20). IEEE Press, Article 36.

Kaiming Ouyang, Min Si, Atsushi Hori, Zizhong Chen, Pavan Balaji. 2021. "Daps: A dynamic asynchronous progress stealing model for mpi communication," In Proceedings of 2021 IEEE International Conference on Cluster Computing (CLUSTER).

Atsushi Hori, Kaiming Ouyang, Balazs Georfi, Yutaka Ishikawa. 2021. "On the Difference between Shared Memory and Shared Address Space in HPC Communication," In Proceedings of Supercomputing Asia 2022, Springer LNCS 13214 2022.

Commands

  • pip-check
  • pip-exec
  • pip-man
  • pip-mode
  • pip-tgkill
  • pipcc
  • pipfc
  • pips
  • printpipmode

Functions

  • pip_abort
  • pip_barrier_fin
  • pip_barrier_init
  • pip_barrier_wait
  • pip_exit
  • pip_export
  • pip_fin
  • pip_get_aux
  • pip_get_mode
  • pip_get_mode_str
  • pip_get_ntasks
  • pip_get_pipid
  • pip_get_system_id
  • pip_import
  • pip_init
  • pip_is_initialized
  • pip_is_shared_fd
  • pip_is_threaded
  • pip_isa_root
  • pip_isa_task
  • pip_kill
  • pip_kill_all_child_tasks
  • pip_named_export
  • pip_named_import
  • pip_named_tryimport
  • pip_set_aux
  • pip_sigmask
  • pip_signal_wait
  • pip_spawn
  • pip_spawn_from_func
  • pip_spawn_from_main
  • pip_spawn_hook
  • pip_task_spawn
  • pip_trywait
  • pip_trywait_any
  • pip_wait
  • pip_wait_any
  • pip_yield

Author

Atsushi Hori

procinproc.github.io's People

Contributors

n-soda avatar ahori avatar

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