> Does anybody actually use "find_package(midas)", does it actually work for anybody?

What we do is to include midas as a submodule and than we call find_package:

    add_subdirectory(midas)
    list(APPEND CMAKE_PREFIX_PATH ${CMAKE_CURRENT_SOURCE_DIR}/midas)
    find_package(Midas REQUIRED)

For us it works fine like this but we kind of always compile Midas fresh and don't use a version on our system (keeping the newest version). 

Without the find_package the build does not work for us.

> > Does anybody actually use "find_package(midas)", does it actually work for anybody?
> 
> What we do is to include midas as a submodule and than we call find_package:
> 
>     add_subdirectory(midas)
>     list(APPEND CMAKE_PREFIX_PATH ${CMAKE_CURRENT_SOURCE_DIR}/midas)
>     find_package(Midas REQUIRED)
> 
> For us it works fine like this but we kind of always compile Midas fresh and don't use a version on our system (keeping the newest version). 
> 
> Without the find_package the build does not work for us.

Ok, I see. I now think that for us, this "find_package" business an unnecessary complication:

since one has to know where midas is in order to add it to CMAKE_PREFIX_PATH,
one might as well import the midas targets directly by include(.../midas/lib/midas-targets.cmake).

From what I see now, the cmake file is much simplifed by converting
it from "find_package(midas)" style MIDAS_INCLUDES & co to more cmake-ish
target_link_libraries(myexe midas) - all the compiler switches, include paths,
dependant libraires and gunk are handled by cmake automatically.

I am not touching the "find_package(midas)" business, so it should continue to work, then.

K.O.

MidasConfig.cmake might at some point get included in the standard Cmake installation (or some add-on). It will then reside in the Cmake system path 
and you don't have to explicitly know where this is. Just the find_package(Midas) will then be enough. 

Even if it's not there, the find_package() is the "traditional" way CMake discovers external packages and users are used to that (like ROOT does the 
same). In comparison, your "midas-targets.cmake" way of doing things, although this works certainly fine, is not the "standard" way, but a midas-
specific solution, other people have to learn extra.

Stefan

> MidasConfig.cmake might at some point get included in the standard Cmake installation (or some add-on). It will then reside in the Cmake system path 
> and you don't have to explicitly know where this is. Just the find_package(Midas) will then be enough.

Hi, Stefan, can you say more about this? If MidasConfig.cmake is part of the cmake distribution,
(did I understand you right here?) and is installed into a system-wide directory,
how can it know to use midas from /home/agmini/packages/midas or from /home/olchansk/git/midas?

Certainly we do not do system wide install of midas (into /usr/local/bin or whatever) because
typically different experiments running on the same computer use different versions of midas.

For ROOT, it looks as if for find_package(ROOT) to work, one has to add $ROOTSYS to the Cmake package
search path. This is what we do in our cmake build.

As for find_package() vs install(EXPORT), we may have the same situation as with my "make cmake",
where my one line solution is no good for people who prefer to type 3 lines of commands.

Specifically, the install(EXPORT) method defines the "midas" target which brings with it
all it's dependent include paths, libraries and compile flags. So to link midas you need
two lines:

include(.../midas/lib/midas-targets.cmake)
target_link_libraries(myexe midas)
target_link_libraries(myfrontend mfe)

whereas find_package() defines a bunch of variables (the best I can tell) and one has
to add them to the include paths and library paths and compile flags "by hand".

I do not know how find_package() handles the separate libmidas, libmfe and librmana. (and
the separate libmanalyzer and libmanalyzer_main).

K.O.

> A simple program to forward MIDAS messages to Discord, Slack and or Mattermost
> 
> (Python 3 required)
> 
> Pull request accepted! Documentation can be found on the wiki
> 
> https://midas.triumf.ca/MidasWiki/index.php/Mmessenger

This sounds like a very useful and welcome addition to MIDAS.

But from documentation provided, I have clue how to activate it.

Perhaps it would help if you could write up the basic steps on how to go about it, i.e.
- go to discord
- push these buttons
- cut and paste this thingy from the web page to ODB

K.O.

> is there any way to order the labels in the history plot legend? In the old 
> system there was the “order” column in the config panel, but I can not find it 
> in the new system. Thanks in advance for the support.

correct, for reasons unknown, the function to reorder and to delete individual 
entries was removed from the history panel editor.

K.O.

> > is there any way to order the labels in the history plot legend? In the old 
> > system there was the “order” column in the config panel, but I can not find it 
> > in the new system. Thanks in advance for the support.
> 
> correct, for reasons unknown, the function to reorder and to delete individual 
> entries was removed from the history panel editor.
> 
> K.O.

https://bitbucket.org/tmidas/midas/issues/284/history-panel-editor-reordering-of

K.O.

I truncated the bitbucket build to only build on ubuntu LTS 20.04.

Somehow all the other build targets - centos-7, centos-8, ubuntu-18 - have
an obsolete version of cmake. I do not know where the bitbucket os images
get these obsolete versions of cmake - my centos-7 and centos-8 have much
more recent versions of cmake.

If somebody has time to figure it out, please go at it, I would like very
much to have centos-7 and centos-8 builds restored (with ROOT), also
to have a ubuntu LTS 20.04 build with ROOT. (For me, debugging bitbucket
builds is extremely time consuming).

Right now many midas cmake files require cmake 3.12 (released in late 2018).

I do not know why that particular version of cmake (I took the number
from the tutorials I used).

I do not know what is the actual version of cmake that MIDAS (and ROOTANA) 
require/depend on.

I wish there were a tool that would look at a cmake file, examine all the 
features it uses and report the lowest version of cmake that supports them.

K.O.

> find_package(Midas)

I am testing find_package(Midas). There is a number of problems:

1) ${MIDAS_LIBRARIES} is set to "midas;midas-shared;midas-c-compat;mfe".

This seem to be an incomplete list of all libraries build by midas (rmana is missing).

This means ${MIDAS_LIBRARIES} should not be used for linking midas programs (unlike ${ROOT_LIBRARIES}, etc):

- we discourage use of midas shared library because it always leads to problems with shared library version mismatch (static linking is preferred)
- midas-c-compat is for building python interfaces, not for linking midas programs
- mfe contains a main() function, it will collide with the user main() function

So I think this should be changed to just "midas" and midas linking dependancy
libraries (-lutil, -lrt, -lpthread) should also be added to this list.

Of course the "install(EXPORT)" method does all this automatically. (so my fixing find_package(Midas) is a waste of time)

2) ${MIDAS_INCLUDE_DIRS} is missing the mxml, mjson, mvodb, midasio submodule directories

Again, install(EXPORT) handles all this automatically, in find_package(Midas) it has to be done by hand.

Anyhow, this is easy to add, but it does me no good in the rootana cmake if I want to build against old versions
of midas. So in the rootana cmake, I still have to add $MIDASSYS/mvodb & co by hand. Messy.

I do not know the history of cmake and why they have two ways of doing things (find_package and install(EXPORT)),
this second method seems to be much simpler, everything is exported automatically into one file,
and it is much easier to use (include the export file and say target_link_libraries(rootana PUBLIC midas)).

So how much time should I spend in fixing find_package(Midas) to make it generally usable?

- include path is incomplete
- library list is nonsense
- compiler flags are not exported (we do not need -DOS_LINUX, but we do need -DHAVE_ZLIB, etc)
- dependency libraries are not exported (-lz, -lutil, -lrt, -lpthread, etc)

K.O.

> > find_package(Midas)
> 
> So how much time should I spend in fixing find_package(Midas) to make it generally usable?
> 
> - include path is incomplete
> - library list is nonsense
> - compiler flags are not exported (we do not need -DOS_LINUX, but we do need -DHAVE_ZLIB, etc)
> - dependency libraries are not exported (-lz, -lutil, -lrt, -lpthread, etc)
> 

I think I give up on find_package(Midas). It seems like a lot of work to straighten
all this out, when install(EXPORT) does it all automatically and is easier to use
for building user frontends and analyzers.

K.O.

Now we are converting the alpha-g event builder from rev0 tmfe (midas-2020-xx) to the new tmfe c++
framework in midas-develop. Earlier, I followed the steps outlined in this blog
to convert this event builder from mfe.c framework to rev0 tmfe.

- get latest midas-develop
- examine progs/tmfe_example_everything.cxx
- open feevb.cxx
- comment-out existing main() function
- from tmfe_example_everything.cxx, copy class FeEverything and main() to the bottom of feevb.cxx
- comment-out old main()
- make sure we include the correct #include "tmfe.h"
- rename example frontend class FeEverything to FeEvb
- rename feevb's "rpc handler" and "periodic handler" class EvbEq to EqEvb
- update class declaration and constructor of EqEvb from EqEverything in example_everything: EqEvb extends TMFeEquipment, 
EqEvb constructor calls constructor of base class (c++ bogosity), keep the bits of the example that initialize the 
equipment "common"
- in EqEvb, remove data members fMfe and fEq: fMfe is now inherited from the base class, fEq is now "this"
- in FeEvb constructor, wire-in the EqEvb constructor: FeSetName("feevb") and FeAddEquipment(new EqEvb("EVB",__FILE__))
- migrate function names:
- fEq->SendEvent() with EqSendEvent()
- fEq->SetStatus() with EqSetStatus()
- fEq->ZeroStatistics() with EqZeroStatistics() -- can be removed, taken care of in the framework
- fEq->WriteStatistics() with EqWriteStatistics() -- can be removed, taken care of in the framework
- (my feevb.o now compiles, but will not work, yet, keep going:)
- EqEvb - update prototypes of all HandleFoo() methods per example_everything.cxx or per tmfe.h: otherwise the framework 
will not call them. c++ compiler will not warn about this!
- migrate old main():
- restore initialization of "common" and other things done in the old main():
- TMFeCommon was merged into TMFeEquipment, move common->Foo = ... to the EqEvb constructor, consult tmfe.h and tmfe.md 
for current variable names.
- consider adding "fEqConfReadConfigFromOdb = false;" (see tmfe.md)
- if EqEvb has a method Init() called from old main(), change it's name to HandleInit() with correct arguments.
- split EqEvb constructor: leave initialization of "common" in the constructor, move all functions, etc into HandleInit()
- move fMfe->SetTransitionSequenceFoo() calls to HandleFrontendInit()
- move fMfe->DeregisterTransition{Pause,Resume}() to HandleFrontendInit()
- old main should be empty now
- remove linking tmfe_rev0.o from feevb Makefile, now it builds!
- try to run it!
- it works!
- done.

K.O.

I am sure everybody else has 10gige and 40gige networks and are sending terabytes of data before breakfast.

Myself, I only have one computer with a 10gige network link and sufficient number of daq boards to fill
it with data. Here is my success story of getting all this data through MIDAS.

This is the anti-matter experiment ALPHA-g now under final assembly at CERN. The main particle detector is a long but 
thin cylindrical TPC. It surrounds the magnetic bottle (particle trap) where we make and study anti-hydrogen. There are 
64 daq boards to read the TPC cathode pads and 8 daq boards to read the anode wires and to form the trigger. Each daq 
board can produce data at 80-90 Mbytes/sec (1gige links). Data is sent as UDP packets (no jumbo frames). Altera FPGA 
firmware was done here at TRIUMF by Bryerton Shaw, Chris Pearson, Yair Lynn and myself.

Network interconnect is a 96-port Juniper switch with a 10gige uplink to the main daq computer (quad core Intel(R) 
Xeon(R) CPU E3-1245 v6 @ 3.70GHz, 64 GBytes of DDR4 memory).

MIDAS data path is: UDP packet receiver frontend -> event builder -> mlogger -> disk -> lazylogger -> CERN EOS cloud 
storage.

First chore was to get all the UDP packets into the main computer. "U" in UDP stands for "unreliable", and at first, UDP 
packets have been disappearing pretty much anywhere they could. To fix this, in order:

- reading from the udp socket must be done in a dedicated thread (in the midas context, pauses to write statistics or 
check alarms result in lost udp packets)
- udp socket buffer has to be very big
- maximum queue sizes must be enabled in the 10gige NIC
- ethernet flow control must be enabled on the 10gige link
- ethernet flow control must be enabled in the switch (to my surprise many switches do not have working end-to-end 
ethernet flow control and lose UDP packets, ask me about this. our big juniper switch balked at first, but I got it 
working eventually).
- ethernet flow control must be enabled on the 1gige links to each daq module
- ethernet flow control must be enabled in the FPGA firmware (it's a checkbox in qsys)
- FPGA firmware internally must have working back pressure and flow control (avalon and axi buses)
- ideally, this back-pressure should feed back to the trigger. ALPHA-g does not have this (it does not need it).

Next chore was to multithread the UDP receiver frontend and to multithread the event builder. Stock single-threaded 
programs quickly max out with 100% CPU use and reach nowhere near 10gige data speeds.

Naive multithreading, with two threads, reader (read UDP packet, lock a mutex, put it into a deque, unlock, repeat) and 
sender (lock a mutex, get a packet from deque, unlock, bm_send_event(), repeat) spends all it's time locking and 
unlocking the mutex and goes nowhere fast (with 1500 byte packets, about 600 kHz of lock/unlock at 10gige speed).

So one has to do everything in batches: reader thread: accumulate 1000 udp packets in an std::vector, lock the mutex, 
dump this batch into a deque, unlock, repeat; sender thread: lock mutex, get 1000 packets from the deque, unlock, stuff 
the 1000 packets into 1 midas event, bm_send_event(), repeat.

It takes me 5 of these multithreaded udp reader frontends to keep up with a 10gige link without dropping any UDP packets. 
My first implementation chewed up 500% CPU, that's all of it, there is only 4 CPU cores available, leaving nothing
for the event builder (and mlogger, and ...)

I had to:
a) switch from plain socket read() to socket recvmmsg() - 100000 udp packets per syscall vs 1 packet per syscall, and
b) switch from plain bm_send_event() to bm_send_event_sg() - using a scatter-gather list to avoid a memcpy() of each udp 
packet into one big midas event.

Next is the event builder.

The event builder needs to read data from the 5 midas event buffers (one buffer per udp reader frontend, each midas event 
contains 1000 udp packets as indovidual data banks), examine trigger timestamps inside each udp packet, collect udp 
packets with matching timestamps into a physics event, bm_send_event() it to the SYSTEM buffer. rinse and repeat.

Initial single threaded implementation maxed out at about 100-200 Mbytes/sec with 100% busy CPU.

After trying several threading schemes, the final implementation has these threads:
- 5 threads to read the 5 event buffers, these threads also examine the udp packets, extract timestamps, etc
- 1 thread to sort udp packets by timestamp and to collect them into physics events
- 1 thread to bm_send_event() physics events to the SYSTEM buffer
- main thread and rpc handler thread (tmfe frontend)

(Again, to reduce lock contention, all data is passed between threads in large batches)

This got me up to about 800 Mbytes/sec. To get more, I had to switch the event builder from old plain bm_send_event() to 
the scatter-gather bm_send_event_sg(), *and* I had to reduce CPU use by other programs, see steps (a) and (b) above.

So, at the end, success, full 10gige data rate from daq boards to the MIDAS SYSTEM buffer.

(But wait, what about the mlogger? In this experiment, we do not have a disk storage array to sink this
much data. But it is an already-solved problem. On the data storage machines I built for GRIFFIN - 8 SATA NAS HDDs using 
raidz2 ZFS - the stock MIDAS mlogger can easily sink 1000 Mbytes/sec from SYSTEM buffer to disk).

Lessons learned:

- do not use UDP. dealing with packet loss will cost you a fortune in headache medicines and hair restorations.
- use jumbo frames. difference in per-packet overhead between 1500 byte and 9000 byte packets is almost a factor of 10.
- everything has to be done in bulk to reduce per-packet overheads. recvmmsg(), batched queue push/pop, etc
- avoid memory allocations (I has a per-packet std::string, replaced it with char[5])
- avoid memcpy(), use writev(), bm_send_event_sg() & co

K.O.

P.S. Let's counting the number of data copies in this system:

x udp reader frontend:
- ethernet NIC DMA into linux network buffers
- recvmmsg() memcpy() from linux network buffer to my memory
- bm_send_event_sg() memcpy() from my memory to the MIDAS shared memory event buffer

x event builder:
- bm_receive_event() memcpy() from MIDAS shared memory event buffer to my event buffer
- my memcpy() from my event buffer to my per-udp-packet buffers
- bm_send_event_sg() memcpy() from my per-udp-packet buffers to the MIDAS shared memory event buffer (SYSTEM)

x mlogger:
- bm_receive_event() memcpy() from MIDAS SYSTEM buffer
- memcpy() in the LZ4 data compressor
- write() syscall memcpy() to linux system disk buffer
- SATA interface DMA from linux system disk buffer to disk.

Would a monolithic massively multithreaded daq application be more efficient?
("udp receiver + event builder + logger"). Yes, about 4 memcpy() out of about 10 will go away.

Would I be able to write such a monolithic daq application?

I think not. Already, at 10gige data rates, for all practical purposes, it is impossible
to debug most problems, especially subtle trouble in multithreading (race conditions)
and in memory allocations. At best, I can sprinkle assert()s and look at core dumps.

So the good old divide-and-conquer approach is still required, MIDAS still rules.

K.O.

In MEG II we also kind of achieved this rate. Marco F. will post an entry soon to describe the details. There is only one thing 
I want to mention, which is our network switch. Instead of an expensive high-grade switch, we chose a cheap "Chinese" high-grade 
switch. We have "rack switches", which are collector switch for each rack receiving up to 10 x 1GBit inputs, and outputting 1 x 
10 GBit to an "aggregation switch", which collects all 10 GBit lines form rack switches and forwards it with (currently a single 
) 10 GBit line. For the rack switch we use a 

MikroTik CRS354-48G-4S+2Q+RM 54 port

and for the aggregation switch

MikroTik CRS326-24S-2Q+RM 26 Port

both cost in the order of 500 US$. We were astonished that they don't loose UDP packets when all inputs send a packet at the 
same time, and they have to pipe them to the single output one after the other, but apparently the switch have enough buffers 
(which is usually NOT written in the data sheets). 

To avoid UDP packet loss for several events, we do traffic shaping by arming the trigger only when the previous event is 
completely received by the frontend. This eliminates all flow control and other complicated methods. Marco can tell you the 
details.

Another interesting aspect: While we get the data into the frontend, we have problems in getting it through midas. Your 
bm_send_event_sg() is maybe a good approach which we should try. To benchmark the out-of-the-box midas, I run the dummy frontend 
attached on my MacBook Pro 2.4 GHz, 4 cores, 16 GB RAM, 1 TB SSD disk. I got

Event size: 7 MB

No logging: 900 events/s = 6.7 GBytes/s

Logging with LZ4 compression: 155 events/s = 1.2 GBytes/s

Logging without compression: 170 events/s = 1.3 GBytes/s

So with this simple approach I got already more than 1 GByte of "dummy data" through midas, indicating that the buffer 
management is not so bad. I did use the plain mfe.c frontend framework, no bm_send_event_sg() (but mfe.c uses rpc_send_event() which is an 
optimized version of bm_send_event()).

Best,
Stefan

As reported by Stefan, in MEG II we have very similar ethernet throughputs.
In total, we have 34 crates each with 32 DRS4 digitiser chips and a single 1 Gbps readout link through a Xilinx Zynq SoC.
The data arrives in push mode without any external intervention, the only throttling being an optional prescaling on the trigger rate.
We discovered the hard way that 1 Gbps throughput on Zynq is not trivial at all: the embedded ethernet MAC does not support jumbo frames (always read the fine prints in the manuals!) and the embedded Linux ethernet stack seems to struggle when we go beyond 250 Mbps of UDP traffic.

Anyhow, even with the reduced speed, the maximum throughput at network input is around 8.5 Gbps which passes through the Mikrotik switches mentioned by Stefan.
We had very bad experiences in the past with similar price-point switches, observing huge packet drops when the instantaneous switching capacity cannot cope with the traffic, but so far we are happy with the Mikrotik ones.

On the receiver side, we have the DAQ server with an Intel E5-2630 v4 CPU and a 10 Gbit connection to the network using an Intel X710 Network card.
In the past, we used also a "cheap" 10 Gbit card from Tehuti but the driver performance was so bad that it could not digest more than 5 Gbps of data.

The current frontend is based on the mfe.c scheme for historical reasons (the very first version dates back to 2015).
We opted for a monolithic multithread solution so we can reuse the underlying DAQ code for other experiments which may not have the complete Midas backend.
Just to mention them: one is the FOOT experiment (which afaik uses an adapted version of Altas DAQ) and the other is the LOLX experiment (for which we are going to ship to Canada soon a small 32 channel system using Midas).
A major modification to Konstantin scheme is that we need to calibrate all WFMs online so that a software zero suppression can be applied to reduce the final data size (that part is still to be implemented).
This requirement results in additional resource usage to parse the UDP content into floats and calibrate them.
Currently, we have 7 packet collector threads to digest the full packet flow (using recvmmsg), followed by an event building stage that uses 4 threads and 3 other threads for WFM calibration.
We have progressive packet numbers on each packet generated by the hardware and a set of flags marking the start and end of the event; combining the packet number difference between the start and end of the event and the total received packets for that event it is really easy to understand if packet drops are happening.

All the thread infrastructure was tested and we could digest the complete throughput, we still have to finalise the full 10 Gbit connection to Midas because the final system has been installed only recently (April).
We are using EQ_USER flag to push events into mfe.c buffers with up to 4 threads, but I was observing that above ~1.5 Gbps the rb_get_wp() returns almost always DB_TIMEOUT and I'm forced to drop the event.
This conflicts with the measurements reported by Stefan (we were discussing this yesterday), so we are still investigating the possible cause.

It is difficult to report three years of development in a single Elog, I hope I put all the relevant point here.
It looks to me that we opted for very complementary approaches for high throughput ethernet with Midas, and I think there are still a lot of details that could be worth reporting.
In case someone organises some kind of "virtual workshop" on this, I'm willing to participate.
Best,

Marco


> In MEG II we also kind of achieved this rate. Marco F. will post an entry soon to describe the details. There is only one thing 
> I want to mention, which is our network switch. Instead of an expensive high-grade switch, we chose a cheap "Chinese" high-grade 
> switch. We have "rack switches", which are collector switch for each rack receiving up to 10 x 1GBit inputs, and outputting 1 x 
> 10 GBit to an "aggregation switch", which collects all 10 GBit lines form rack switches and forwards it with (currently a single 
> ) 10 GBit line. For the rack switch we use a 
> 
> MikroTik CRS354-48G-4S+2Q+RM 54 port
> 
> and for the aggregation switch
> 
> MikroTik CRS326-24S-2Q+RM 26 Port
> 
> both cost in the order of 500 US$. We were astonished that they don't loose UDP packets when all inputs send a packet at the 
> same time, and they have to pipe them to the single output one after the other, but apparently the switch have enough buffers 
> (which is usually NOT written in the data sheets). 
> 
> To avoid UDP packet loss for several events, we do traffic shaping by arming the trigger only when the previous event is 
> completely received by the frontend. This eliminates all flow control and other complicated methods. Marco can tell you the 
> details.
> 
> Another interesting aspect: While we get the data into the frontend, we have problems in getting it through midas. Your 
> bm_send_event_sg() is maybe a good approach which we should try. To benchmark the out-of-the-box midas, I run the dummy frontend 
> attached on my MacBook Pro 2.4 GHz, 4 cores, 16 GB RAM, 1 TB SSD disk. I got
> 
> Event size: 7 MB
> 
> No logging: 900 events/s = 6.7 GBytes/s
> 
> Logging with LZ4 compression: 155 events/s = 1.2 GBytes/s
> 
> Logging without compression: 170 events/s = 1.3 GBytes/s
> 
> So with this simple approach I got already more than 1 GByte of "dummy data" through midas, indicating that the buffer 
> management is not so bad. I did use the plain mfe.c frontend framework, no bm_send_event_sg() (but mfe.c uses rpc_send_event() which is an 
> optimized version of bm_send_event()).
> 
> Best,
> Stefan

mlogger (history_image) now supports rtsp cameras, in ALPHA we have 
acquisitioned several new network connected cameras. Unfortunately they dont 
have a way of just capturing a single frame using libcurl


========================================
Motivation to link to OpenCV libraries
========================================

After looking at the ffmpeg libraries, it seemed non trivial to use them to 
listen to a rtsp stream and write a series of jpgs.

OpenCV became an obvious choice (it is itself linked to ffmpeg and 
gstreamer), its a popular, multiplatform, open source library that's easy to 
use. It is available in the default package managers in centos 7 and ubuntu 
(an is installed by default on lxplus).

========================================
How it works:
========================================

The framework laid out in history_image.cxx is great. A separate thread is 
dedicated for each camera. This is continued with the rtsp support, using 
the same periodicity:

if (ss_time() >= o["Last fetch"] + o["Period"]) {
An rtsp camera is detected by its URL, if the URL starts with ‘rtsp://’ its 
obvious its using the rtsp protocol and the cv::VideoCapture object is 
created (line 147).

If the connection fails, it will continue to retry, but only send an error 
message on the first 10 attempts (line 150). This counter is reset on 
successful connection
If MIDAS has been built without OpenCV, mlogger will send an error message 
that OpenCV is required if a rtsp URL is given (line 166)
The VideoCapture ‘stays live' and will grab frames from the camera based on 
the sleep, saving to file based on the Period set in the ODB.

If the VideoCapture object is unable to grab a frame, it will release() the 
camera, send an error message to MIDAS, then destroy itself, and create a 
new version (this destroy and create fully resets the connection to a 
camera, required if its on flaky wifi)
If the VideoCapture gets an empty frame, it also follows the same reset 
steps.
If the VideoCaption fills a cv::Frame object successfully, the image is 
saved to disk in the same way as the curl tools.

========================================
Concerns for the future:
========================================

VideoCapture is decoding the video stream in the background, allowing us to 
grab frames at will. This is nice as we can be pretty agnostic to the video 
format in the stream (I tested with h264 from a TP-LINK TAPO C100, but the 
CPU usage is not negligible.

I noticed that this used ~2% of the CPU time on an intel i7-4770 CPU, given 
enough cameras this is considerable. In ALPHA, I have been testing with 10 
cameras:
elog:2220/1 

My suggestion / request would be to move the camera management out of 
mlogger and into a new program (mcamera?), so that users can choose to off 
load the CPU load to another system (I understand the OpenCV will use GPU 
decoders if available also, which can also lighten the CPU load).

> In MEG II we also kind of achieved this rate.
>
> Instead of an expensive high-grade switch, we chose a cheap "Chinese" high-grade switch.

Right. We built this DAQ system about 3 years ago and the cheep Chineese switches arrived
on the market about 1 year after we purchased the big 96 port juniper switch. Bad timing/good timing.

Actually I have a very nice 24-port 1gige switch ($2000 about 3 years ago), I could have
used 4 of them in parallel, but they were discontinued and replaced with a $5000 switch
(+$3000 for a 10gige uplink. I think I got the last very last one cheap switch).

But not all Chineese switches are equal. We have an Ubiquity 10gige switch, and it does
not have working end-to-end ethernet flow control. (yikes!).

BTW, for this project we could not use just any cheap switch, we must have 64 fiber SFP ports
for connecting on-TPC electronics. This narrows the market significantly and it does
not match the industry standard port counts 8-16-24-48-96.

> MikroTik CRS354-48G-4S+2Q+RM 54 port
> MikroTik CRS326-24S-2Q+RM 26 Port

We have a hard time buying this stuff in Vancouver BC, Canada. Most of our regular suppliers
are US based and there is a technology trade war still going on between the US and China.
I guess we could buy direct on alibaba, but for the risk of scammers, scalpers and iffy shipping.

> both cost in the order of 500 US$

tell one how much we overpay for US based stuff. not surprising, with how Cisco & co can afford
to buy sports arenas, etc.

> We were astonished that they don't loose UDP packets when all inputs send a packet at the 
> same time, and they have to pipe them to the single output one after the other,
> but apparently the switch have enough buffers.

You probably see ethernet flow control in action. Look at the counters for ethernet pause frames
in your daq boards and in your main computer.

> (which is usually NOT written in the data sheets).

True, when I looked into this, I found a paper by somebody in Berkley for special
technique to measure the size of such buffers.

(The big Juniper switch has only 8 Mbytes of buffer. The current wisdom for backbone networks
is to have as little buffering as possible).

> To avoid UDP packet loss for several events, we do traffic shaping by arming the trigger only when the previous event is 
> completely received by the frontend. This eliminates all flow control and other complicated methods. Marco can tell you the 
> details.

We do not do this. (very bad!). When each trigger arrives, all 64+8 DAQ boards send a train of UDP packets
at maximum line speed (64+8 at 1 gige) all funneled into one 10 gige ((64+8)/10 oversubscription).

Before we got ethernet flow control to work properly, we had to throttle all the 1gige links by about 60%
to get any complete events at all. This would not have been acceptable for physics data taking.

> Another interesting aspect: While we get the data into the frontend, we have problems in getting it through midas. Your 
> bm_send_event_sg() is maybe a good approach which we should try. To benchmark the out-of-the-box midas, I run the dummy frontend 
> attached on my MacBook Pro 2.4 GHz, 4 cores, 16 GB RAM, 1 TB SSD disk.

Dummy frontend is not very representative, because limitation is the memory bandwidth
and CPU load, and a real ethernet receiver has quite a bit of both (interrupt processing,
DMA into memory, implicit memcpy() inside the socket read()).

For example, typical memcpy() speeds are between 22 and 10 Gbytes/sec for current
generation CPUs and DRAM. This translates for a total budget of 22 and 10 memcpy()
at 10gige speeds. Subtract from this 1 memcpy() to DMA data from ethernet into memory
and 1 memcpy() to DMA data from memory to storage. Subtract from this 2 implicit
memcpy() for read() in the frontend and write() in mlogger. (the Linux sendfile() syscall
was invented to cut them out). Subtract from this 1 memcpy() for instruction and incidental
data fetch (no interesting program fits into cache). Subtract from this memory bandwidth
for running the rest of linux (systemd, ssh, cron jobs, NFS, etc). Hardly anything
left when all is said and done. (Found it, the alphagdaq memcpy() runs at 14 Gbytes/sec,
so total budget of 14 memcpy() at 10gige speeds).

And the event builder eats up 2 CPU cores to process the UDP packets at 10gige rate,
there is quite a bit of CPU-expensive data unpacking, inspection and processing
going on that cannot be cut out. (alphagdaq has 4 cores, "8 threads").

K.O.

P.S. Waiting for rack-mounted machines with AMD "X" series processors... K.O.

> ... MEG II ... 34 crates each with 32 DRS4 digitiser chips and a single 1 Gbps readout link through a Xilinx Zynq SoC.
>
> Zynq ... embedded ethernet MAC does not support jumbo frames (always read the fine prints in the manuals!)
> and the embedded Linux ethernet stack seems to struggle when we go beyond 250 Mbps of UDP traffic.

that's an ouch. we use the altera ethernet mac, and jumbo frames are supported, but the firmware data path
was originally written assuming 1500-byte packets and it is too much work to rewrite it for jumbo frames.

we send the data directly from the FPGA fabric to the ethernet, there is an avalon/axi bus multiplexer
to split the ethernet packets to the NIOS slow control CPU. not sure if such scheme is possible
for SoC FPGAs with embedded ARM CPUs.

and yes, a 1 GHz ARM CPU will not do 10gige. You see it yourself, measure your memcpy() speed. Where
typical PC will have dual-channel 128-bit wide memory (and the famous for it's low latency
Intel memory controller), ARM SoC will have at best 64-bit wide memory (some boards are only 32-bit wide!),
with DDR3 (not DDR4) severely under-clocked (i.e. DDR3-900, etc). This is why the new Apple ARM chips
are so interesting - can Apple ARM memory controller beat the Intel x86 memory controller?

> On the receiver side, we have the DAQ server with an Intel E5-2630 v4 CPU

that's the right gear for the job. quad-channel memory with nominal "Max Memory Bandwidth 68.3 GB/s",
10 CPU cores. My benchmark of memcpy() for the much older duad-channel memory i7-4820 with DDR3-1600 DIMMs
is 20 Gbytes/sec. waiting for ARM CPU with similar specs.

> and a 10 Gbit connection to the network using an Intel X710 Network card.
> In the past, we used also a "cheap" 10 Gbit card from Tehuti but the driver performance was so bad that it could not digest more than 5 Gbps of data.

yup, same here. use Intel ethernet exclusively, even for 1gige links.

> A major modification to Konstantin scheme is that we need to calibrate all WFMs online so that a software zero suppression

I implemented hardware zero suppression in the FPGA code. I think 1 GHz ARM CPU does not have the oomph for this.

> rb_get_wp() returns almost always DB_TIMEOUT

replace rb_xxx() with std::deque<std::vector<char>> (protected by a mutex, of course). lots of stuff in the mfe.c frontend
is obsolete in the same way. check out the newer tmfe frontends (tmfe.md, tmfe.h and tmfe examples).

> It is difficult to report three years of development in a single Elog

but quite successful at it. big thanks for your write-up. I think our info is quite useful for the next people.

K.O.

> mlogger (history_image) now supports rtsp cameras

my goodness, we will drive the video surveillance industry out of business.

> My suggestion / request would be to move the camera management out of 
> mlogger and into a new program (mcamera?), so that users can choose to off 
> load the CPU load to another system (I understand the OpenCV will use GPU 
> decoders if available also, which can also lighten the CPU load).

every 2 years I itch to separate mlogger into two parts - data logger
and history logger.

but then I remember that the "I" in MIDAS stands for "integrated",
and "M" stands for "maximum" and I say, "nah..."

(I guess we are not maximum integrated enough to have mhttpd, mserver
and mlogger to be one monolithic executable).

There is also a line of thinking that mlogger should remain single-threaded
for maximum reliability and ease of debugging. So if we keep adding multithreaded
stuff to it, perhaps it should be split-apart after all. (anything that makes
the size of mlogger.cxx smaller is a good thing, imo).

K.O.

the day has arrived when I cannot git push to bitbucket. cloud computing rules!

I have never seen this error before and I do not think we have any hooks installed,
so it must be some bitbucket stuff. their status page says some kind of maintenance
is happening, but the promised error message is "repository is read only" or something 
similar.

I hope this clears out automatically. I am updating all the cmake crud and I have no idea 
which changes I already pushed and which I did not, so no idea if anything will work for 
people who pull from midas until this problem is cleared out.

daq00:mvodb$ git push
X11 forwarding request failed on channel 0
Enumerating objects: 3, done.
Counting objects: 100% (3/3), done.
Delta compression using up to 12 threads
Compressing objects: 100% (2/2), done.
Writing objects: 100% (2/2), 247 bytes | 247.00 KiB/s, done.
Total 2 (delta 1), reused 0 (delta 0)
remote: null value in column "attempts" violates not-null constraint
remote: DETAIL:  Failing row contains (13586899, 2021-07-10 01:13:28.812076+00, 1970-01-01 
00:00:00+00, 1970-01-01 00:00:00+00, 65975727, null).
To bitbucket.org:tmidas/mvodb.git
 ! [remote rejected] master -> master (pre-receive hook declined)
error: failed to push some refs to 'git@bitbucket.org:tmidas/mvodb.git'
daq00:mvodb$

K.O.

I reworked the midas cmake files:
- install via CMAKE_INSTALL_PREFIX should work correctly now:
- installed are bin, lib and include - everything needed to build against the midas library
- if built without CMAKE_INSTALL_PREFIX, a special mode "MIDAS_NO_INSTALL_INCLUDE_FILES" is activated, and the include path 
contains all the subdirectories need for compilation
- -I$MIDASSYS/include and -L$MIDASSYS/lib -lmidas work in both cases
- to "use" midas, I recommend: include($ENV{MIDASSYS}/lib/midas-targets.cmake)
- config files generated for find_package(midas) now have correct information (a manually constructed subset of information 
automatically exported by cmake's install(export))
- people who want to use "find_package(midas)" will have to contribute documentation on how to use it (explain the magic used to 
find the "right midas" in /usr/local/midas or in /midas or in ~/packages/midas or in ~/pacjages/new-midas) and contribute an 
example superproject that shows how to use it and that can be run from the bitpucket automatic build. (features that are not part 
of the automatic build we cannot insure against breakage).

On my side, here is an example of using include($ENV{MIDASSYS}/lib/midas-targets.cmake). I posted this before, it is used in 
midas/examples/experiment and I will ask ben to include it into the midas wiki documentation.

Below is the complete cmake file for building the alpha-g event bnuilder and main control frontend. When presented like this, I 
have to agree that cmake does provide positive value to the user. (the jury is still out whether it balances out against the 
negative value in the extra work to "just support find_package(midas) already!").

#
# CMakeLists.txt for alpha-g frontends
#

cmake_minimum_required(VERSION 3.12)
project(agdaq_frontends)

include($ENV{MIDASSYS}/lib/midas-targets.cmake)

add_compile_options("-O2")
add_compile_options("-g")
#add_compile_options("-std=c++11")
add_compile_options(-Wall -Wformat=2 -Wno-format-nonliteral -Wno-strict-aliasing -Wuninitialized -Wno-unused-function)
add_compile_options("-DTMFE_REV0")
add_compile_options("-DOS_LINUX")

add_executable(feevb feevb.cxx TsSync.cxx)
target_link_libraries(feevb midas)

add_executable(fectrl fectrl.cxx GrifComm.cxx EsperComm.cxx JsonTo.cxx KOtcp.cxx $ENV{MIDASSYS}/src/tmfe_rev0.cxx)
target_link_libraries(fectrl midas)

#end