mirror of
https://github.com/paulscherrerinstitute/sf_daq_buffer.git
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babic_a
dbc913ee78
All references to folders and files inside buffer were updated. - Base folder to write detector: detector_folder - Name of the modules inside detector_folder: module_name - Data grouping folders based on pulse_id: data_folder - Data grouping files, based on pulse_id: data_file
sf_daq_buffer
Overview of current architecture and component interaction.
Useful links
Architecture
- POSIX compliant write order test on GPFS https://svn.hdfgroup.org/hdf5/branches/hdf5_1_10_0/test/POSIX_Order_Write_Test_Report.pdf
- Best Practice Guide - Parallel I/O https://prace-ri.eu/wp-content/uploads/Best-Practice-Guide_Parallel-IO.pdf
- MPI-IO/GPFS, an Optimized Implementation of MPI-IO on top of GPFS https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1592834
- 10GE network tests with UDP - European XFEL https://indico.cern.ch/event/212228/contributions/1507212/attachments/333941/466017/10GE_network_tests_with_UDP.pdf
- How to choose between Kafka and RabbitMQ https://tarunbatra.com/blog/comparison/How-to-choose-between-Kafka-and-RabbitMQ/
Software
- Intro to lock free programming https://preshing.com/20120612/an-introduction-to-lock-free-programming/
- JSON library benchmarks https://github.com/miloyip/nativejson-benchmark
- Kernel bypass https://blog.cloudflare.com/kernel-bypass/
- PACKET_MMAP https://www.kernel.org/doc/Documentation/networking/packet_mmap.txt
- Hyperslab selection https://support.hdfgroup.org/HDF5/Tutor/phypecont.html https://support.hdfgroup.org/HDF5/Tutor/selectsimple.html
- Caching and Buffering in HDF5 https://de.slideshare.net/HDFEOS/caching-and-buffering-in-hdf5
- Chunking in HDF5 https://portal.hdfgroup.org/display/HDF5/Chunking+in+HDF5
- Setting Raw Data Chunk Cache Parameters in HDF5 https://support.hdfgroup.org/pubs/rfcs/RFC_chunk_cache_functions.pdf
- Memory model synchronization modes https://gcc.gnu.org/wiki/Atomic/GCCMM/AtomicSync
- Is Parallel Programming Hard, And, If So, What Can You Do About It? https://mirrors.edge.kernel.org/pub/linux/kernel/people/paulmck/perfbook/perfbook.2018.12.08a.pdf
- Linux kernel profiling with perf https://perf.wiki.kernel.org/index.php/Tutorial
Linux configuration
- CFS: Completely fair process scheduling in Linux https://opensource.com/article/19/2/fair-scheduling-linux
- perf sched for Linux CPU scheduler analysis http://www.brendangregg.com/blog/2017-03-16/perf-sched.html
- Tuning CPU scheduler for reducing latency https://www.scylladb.com/2016/06/10/read-latency-and-scylla-jmx-process/
- RHEL7: How to get started with CGroups. https://www.certdepot.net/rhel7-get-started-cgroups/
- Cpusets https://www.kernel.org/doc/Documentation/cgroup-v1/cpusets.txt
- Understanding mlx5 ethtool Counters https://community.mellanox.com/s/article/understanding-mlx5-ethtool-counters
- Red Hat Enterprise Linux Network Performance Tuning Guide https://access.redhat.com/sites/default/files/attachments/20150325_network_performance_tuning.pdf
- Low latency 10Gbps Ethernet https://blog.cloudflare.com/how-to-achieve-low-latency/
- Monitoring and Tuning the Linux Networking Stack: Receiving Data https://blog.packagecloud.io/eng/2016/06/22/monitoring-tuning-linux-networking-stack-receiving-data/#procnetsoftnet_stat
- Making linux do hard real-time https://www.slideshare.net/jserv/realtime-linux
- Linux timing and scheduling granularity https://fritshoogland.wordpress.com/2018/03/13/linux-timing-and-scheduling-granularity/
- Raw Ethernet Programming: Basic Introduction - Code Example https://community.mellanox.com/s/article/raw-ethernet-programming--basic-introduction---code-example
- Performance Tuning for Mellanox Adapters https://community.mellanox.com/s/article/performance-tuning-for-mellanox-adapters
- UEFI Workload-based Performance and TuningGuide for HPE ProLiant Gen10 https://support.hpe.com/hpesc/public/docDisplay?docId=a00016408en_us
Build
To compile this repo you will need to install the following packages on RH7:
- devtoolset-9
- cmake3
- zeromq-devel
- hdf5-devel
yum install devtoolset-9
yum install cmake3
yum install zeromq-devel
yum install hdf5-devel
Step by step procedure to build the repo:
scl enable devtoolset-9 bash
git clone https://github.com/paulscherrerinstitute/sf_daq_buffer.git
cd sf_daq_buffer
mkdir build
cd build/
cmake3 ..
make
It is recommended to create symbolic links to the executables you will be using inside your PATH.
Example:
ln -s "$(pwd)""/""sf_buffer" /usr/bin/sf_buffer
ln -s "$(pwd)""/""sf_stream" /usr/bin/sf_stream
ln -s "$(pwd)""/""sf_writer" /usr/bin/sf_writer
Warnings
Zeromq
Zeromq version 4.1.4 (default on RH7) has a LINGER bug. Sometimes, the last message is not sent (the connection gets dropped before the message is in the buffer). Since we use PUSH/PULL to modulate the sf_replay speed, this is a key functionality we are using.
Please install a later version:
cd /etc/yum.repos.d/
wget https://download.opensuse.org/repositories/network:messaging:zeromq:release-stable/RHEL_7/network:messaging:zeromq:release-stable.repo
yum remove zeromq
yum remove openpgm
yum install libsodium-devel
yum install zeromq-devel
Terminology
In order to unify the way we write code and talk about concept the following terminology definitions should be followed:
- frame (data from a single module)
- image (data of the assembled image)
- start_pulse_id and stop_pulse_id (not end_pulse_id) is used to determine the inclusive range (both start and stop pulse_id are included) of pulses.
- detector_folder (root folder of the buffer for a specific detector on disk)
- module_name (name of one module inside the detector_folder)
- data_folder (folder where we group more buffer files based on pulse_id range)
Data location in buffer
The written by sf_buffer are saved to:
[detector_folder]/[module_name]/[data_folder]/[data_file].bin
- detector_folder should always be passed as an absolute path.
- module_name is usually composed like "M00", "M01".
- data_folder and data_file are automatically calculated based on the current pulse_id, FOLDER_MOD and FILE_MOD attributes.
// FOLDER_MOD = 100000
int data_folder = (pulse_id % FOLDER_MOD) * FOLDER_MOD;
// FILE_MOD = 1000
int data_file = (pulse_id % FILE_MOD) * FILE_MOD;
FOLDER_MOD == 100000 means that each data_folder will contain data for 100000 pulses, while FILE_MOD == 1000 means that each file inside the data_folder will contain 1000 pulses. The total number of data_files in each data_folder will therefore be FILE_MOD / FOLDER_MOD = 100.