• GRRRR part 2

    From John Larkin@21:1/5 to All on Wed Jun 1 15:38:20 2022
    I'm waiting for a sim to run, so may as well whine. It's running at 12
    PPM of real time.

    LT Spice lets you put the value of a part anywhere on the screen. I
    just spent an embarassing amount of time figuring out why my current
    limiter didn't work. It's a switching half-bridge with an output
    current sensor, and a pair of P+I opamps that sense positive and
    negative over-current and clamp the input demand signal appropriately.

    (The current limit will be in an FPGA, but I like to do an analog sim
    to get the dynamics close.)

    I have a couple of BVs as isolators between the PWM generator and the
    floating (+ and - 48 volt supplies) LTC4444 mosfet gate driver. The
    equations of the BVs were swapped, so my power stage gain was
    reversed. Negative feedback wasn't.

    Some cad software limits how far a ref designator or a value can be
    from the part. Or highlights one if you click on the other.

    More fun: if you copy and paste a chunk of circuit, the copy has all
    the same node names. So everything is shorted to everything until you
    find and change the nodes that matter.

    I'll need to get a new PC soon. People say that a screaming CPU and
    lots of ram and solid-state C drive would really speed things up.

    Hey, it finished. It made a 5.4 Gbyte RAW file.





    --

    If a man will begin with certainties, he shall end with doubts,
    but if he will be content to begin with doubts he shall end in certainties. Francis Bacon

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Jan Panteltje@21:1/5 to jlarkin@highland_atwork_technology. on Thu Jun 2 06:05:25 2022
    On a sunny day (Wed, 01 Jun 2022 15:38:20 -0700) it happened John Larkin <jlarkin@highland_atwork_technology.com> wrote in <m2pf9hp44ssn7vu45eftf46jncjo4ppbp5@4ax.com>:

    I'm waiting for a sim to run, so may as well whine. It's running at 12
    PPM of real time.

    LT Spice lets you put the value of a part anywhere on the screen. I
    just spent an embarassing amount of time figuring out why my current
    limiter didn't work. It's a switching half-bridge with an output
    current sensor, and a pair of P+I opamps that sense positive and
    negative over-current and clamp the input demand signal appropriately.

    (The current limit will be in an FPGA, but I like to do an analog sim
    to get the dynamics close.)

    I have a couple of BVs as isolators between the PWM generator and the >floating (+ and - 48 volt supplies) LTC4444 mosfet gate driver. The
    equations of the BVs were swapped, so my power stage gain was
    reversed. Negative feedback wasn't.

    Some cad software limits how far a ref designator or a value can be
    from the part. Or highlights one if you click on the other.

    More fun: if you copy and paste a chunk of circuit, the copy has all
    the same node names. So everything is shorted to everything until you
    find and change the nodes that matter.

    I'll need to get a new PC soon. People say that a screaming CPU and
    lots of ram and solid-state C drive would really speed things up.

    Hey, it finished. It made a 5.4 Gbyte RAW file.

    There was a headline in scidaily.com today about if AI designed stuff should be patented and by whom, or something

    I know I probably draw fire if I say that all that spice is a dead end road at least for many things.

    Neural networks, done some programming with that, we are like that.. could be the future
    in electronic design too.
    But a NN (Neural Net) is trained by building and testing things.
    Even if you spice on a supper computah there is NO guarantee the circuit will even work in reality.

    I play with Raspberry Pis these days.. Even those are very much unobtainable due to chip or other shortages..
    Would be nice to have LT spice running on ARM processors (maybe there is a port already?)
    There must be a break even point between AI an Spice type simulations for electronic design?
    Wonder how far that is away.
    For the rest I leave the problem solving to my neural net, have not touched spice in years?
    It is nice for filters that need a lot of repeated math scribbling, but there are other filter design programs.
    Many things do not have a good spice model...

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From John Doe@21:1/5 to John Larkin on Thu Jun 2 09:28:24 2022
    John Larkin wrote:

    I'll need to get a new PC soon. People say that a screaming CPU and lots
    of ram and solid-state C drive would really speed things up.

    I have had NVMe drives for ages. Get good ones, like from Samsung. Spend
    more than you used to spend on hard drives, it's well worth it. Primary
    (and secondary) storage is not whizbang fun, but as IBM used to put it, it affects "throughput" more than anything else. NVMe is what I have always wanted.

    If you use a secondary drive, the transfer rate between two premium NVMe
    drives is OUTRAGEOUS. Transferring movies from your downloads folder to
    the secondary drive is quick. Making backups of Windows is also quick.

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From jlarkin@highlandsniptechnology.com@21:1/5 to pNaonStpealmtje@yahoo.com on Thu Jun 2 06:33:32 2022
    On Thu, 02 Jun 2022 06:05:25 GMT, Jan Panteltje
    <pNaonStpealmtje@yahoo.com> wrote:

    On a sunny day (Wed, 01 Jun 2022 15:38:20 -0700) it happened John Larkin ><jlarkin@highland_atwork_technology.com> wrote in ><m2pf9hp44ssn7vu45eftf46jncjo4ppbp5@4ax.com>:

    I'm waiting for a sim to run, so may as well whine. It's running at 12
    PPM of real time.

    LT Spice lets you put the value of a part anywhere on the screen. I
    just spent an embarassing amount of time figuring out why my current >>limiter didn't work. It's a switching half-bridge with an output
    current sensor, and a pair of P+I opamps that sense positive and
    negative over-current and clamp the input demand signal appropriately.

    (The current limit will be in an FPGA, but I like to do an analog sim
    to get the dynamics close.)

    I have a couple of BVs as isolators between the PWM generator and the >>floating (+ and - 48 volt supplies) LTC4444 mosfet gate driver. The >>equations of the BVs were swapped, so my power stage gain was
    reversed. Negative feedback wasn't.

    Some cad software limits how far a ref designator or a value can be
    from the part. Or highlights one if you click on the other.

    More fun: if you copy and paste a chunk of circuit, the copy has all
    the same node names. So everything is shorted to everything until you
    find and change the nodes that matter.

    I'll need to get a new PC soon. People say that a screaming CPU and
    lots of ram and solid-state C drive would really speed things up.

    Hey, it finished. It made a 5.4 Gbyte RAW file.

    There was a headline in scidaily.com today about if AI designed stuff should be patented and by whom, or something

    I know I probably draw fire if I say that all that spice is a dead end road at least for many things.

    It's sure not dead for people who design real electronics. What I want
    is for Spice to run on an Nvidia parallel compute engine, 200x or so
    faster than on an Intel cpu.


    Neural networks, done some programming with that, we are like that.. could be the future
    in electronic design too.
    But a NN (Neural Net) is trained by building and testing things.

    Are NNs anything but an academic toy?

    Even if you spice on a supper computah there is NO guarantee the circuit will even work in reality.

    Sometimes things work exactly as Spiced. Good engineers can usually
    expect when the sims aren't to be trusted.


    I play with Raspberry Pis these days.. Even those are very much unobtainable due to chip or other shortages..
    Would be nice to have LT spice running on ARM processors (maybe there is a port already?)
    There must be a break even point between AI an Spice type simulations for electronic design?
    Wonder how far that is away.

    There have been attempts to use computers to actually design circuits,
    or at least to optimize values in a given topology. They tended to be
    ludicrous failures.

    It's strange that our brains, evolved to be hunter-gatherers, can
    design electronics.

    For the rest I leave the problem solving to my neural net, have not touched spice in years?
    It is nice for filters that need a lot of repeated math scribbling, but there are other filter design programs.
    Many things do not have a good spice model...

    That's the main hazard, not having dependable part models. That's a
    serious problem when using RF-type parts large-signal time domain.

    We finally finished our big laser modulator chassis. The
    amplifier/fiducial board got to rev C, and we avoided D by adding a MiniCircuits SMA DC block in one of the cables. You can't sim this
    fast stuff; just guess and etch.

    https://www.dropbox.com/s/29ttap9urihhep1/T500_Top_Final.jpg?raw=1

    We couldn't get LCD driver chips, but their eval boards are available,
    so we used eval boards.



    --

    Anybody can count to one.

    - Robert Widlar

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From jlarkin@highlandsniptechnology.com@21:1/5 to always.look@message.header on Thu Jun 2 06:36:40 2022
    On Thu, 2 Jun 2022 09:28:24 -0000 (UTC), John Doe
    <always.look@message.header> wrote:

    John Larkin wrote:

    I'll need to get a new PC soon. People say that a screaming CPU and lots
    of ram and solid-state C drive would really speed things up.

    I have had NVMe drives for ages. Get good ones, like from Samsung. Spend
    more than you used to spend on hard drives, it's well worth it. Primary
    (and secondary) storage is not whizbang fun, but as IBM used to put it, it >affects "throughput" more than anything else. NVMe is what I have always >wanted.

    If you use a secondary drive, the transfer rate between two premium NVMe >drives is OUTRAGEOUS. Transferring movies from your downloads folder to
    the secondary drive is quick. Making backups of Windows is also quick.

    I guess one can plug an ssd into a PCIe slot. I need new PCs and it
    would be cool to have a fast D: drive on them, mostly for Dropbox.



    --

    Anybody can count to one.

    - Robert Widlar

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Phil Hobbs@21:1/5 to jlarkin@highlandsniptechnology.com on Thu Jun 2 10:16:40 2022
    jlarkin@highlandsniptechnology.com wrote:
    On Thu, 02 Jun 2022 06:05:25 GMT, Jan Panteltje
    <pNaonStpealmtje@yahoo.com> wrote:
    <snip>


    Neural networks, done some programming with that, we are like
    that.. could be the future in electronic design too. But a NN
    (Neural Net) is trained by building and testing things.

    Are NNs anything but an academic toy?

    They're great for flagging possibilities for later evaluation. IIRC
    they're used in drug discovery for that reason. For control systems,
    not so much.

    Even if you spice on a supper computah there is NO guarantee the
    circuit will even work in reality.

    Sometimes things work exactly as Spiced. Good engineers can usually
    expect when the sims aren't to be trusted.


    I play with Raspberry Pis these days.. Even those are very much
    unobtainable due to chip or other shortages.. Would be nice to have
    LT spice running on ARM processors (maybe there is a port
    already?) There must be a break even point between AI an Spice type
    simulations for electronic design? Wonder how far that is away.

    There have been attempts to use computers to actually design
    circuits, or at least to optimize values in a given topology. They
    tended to be ludicrous failures.

    It's strange that our brains, evolved to be hunter-gatherers, can
    design electronics.

    It's not at all strange that our minds, being made in the image of the
    Maker, can do that. ;)


    For the rest I leave the problem solving to my neural net, have not
    touched spice in years? It is nice for filters that need a lot of
    repeated math scribbling, but there are other filter design
    programs. Many things do not have a good spice model...

    That's the main hazard, not having dependable part models. That's a
    serious problem when using RF-type parts large-signal time domain.

    We finally finished our big laser modulator chassis. The
    amplifier/fiducial board got to rev C, and we avoided D by adding a MiniCircuits SMA DC block in one of the cables. You can't sim this
    fast stuff; just guess and etch.

    https://www.dropbox.com/s/29ttap9urihhep1/T500_Top_Final.jpg?raw=1

    We couldn't get LCD driver chips, but their eval boards are
    available, so we used eval boards.

    There's a lot of that going around.

    Cheers

    Phil Hobbs

    (Who is in the middle of a board spin for our nanowatt photoreceiver,
    partly for that reason.)


    --
    Dr Philip C D Hobbs
    Principal Consultant
    ElectroOptical Innovations LLC / Hobbs ElectroOptics
    Optics, Electro-optics, Photonics, Analog Electronics
    Briarcliff Manor NY 10510

    http://electrooptical.net
    http://hobbs-eo.com

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From bitrex@21:1/5 to jlarkin@highlandsniptechnology.com on Thu Jun 2 11:02:02 2022
    On 6/2/2022 9:36 AM, jlarkin@highlandsniptechnology.com wrote:
    On Thu, 2 Jun 2022 09:28:24 -0000 (UTC), John Doe <always.look@message.header> wrote:

    John Larkin wrote:

    I'll need to get a new PC soon. People say that a screaming CPU and lots >>> of ram and solid-state C drive would really speed things up.

    I have had NVMe drives for ages. Get good ones, like from Samsung. Spend
    more than you used to spend on hard drives, it's well worth it. Primary
    (and secondary) storage is not whizbang fun, but as IBM used to put it, it >> affects "throughput" more than anything else. NVMe is what I have always
    wanted.

    If you use a secondary drive, the transfer rate between two premium NVMe
    drives is OUTRAGEOUS. Transferring movies from your downloads folder to
    the secondary drive is quick. Making backups of Windows is also quick.

    I guess one can plug an ssd into a PCIe slot. I need new PCs and it
    would be cool to have a fast D: drive on them, mostly for Dropbox.


    Cross-probing large .raw files even stored on an SSD is still slow cuz
    they use a compressed format, to make it snappy you have to first
    convert the data file:

    <https://ltwiki.org/LTspiceHelp/LTspiceHelp/Fast_Access_File_Format.htm>

    which is also slow. Or with your new machine you can buy a bunch of RAM
    say 32 or 64 gig and make half of it a RAM drive dedicated to sim data
    which also speeds up probing considerably.

    64 gig of DDR5 is about $500 and $250 for 64 gig of DDR4 on Amazon these
    days.

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Anthony William Sloman@21:1/5 to jla...@highlandsniptechnology.com on Thu Jun 2 10:01:00 2022
    On Thursday, June 2, 2022 at 11:36:51 PM UTC+10, jla...@highlandsniptechnology.com wrote:
    On Thu, 2 Jun 2022 09:28:24 -0000 (UTC), John Doe
    <alway...@message.header> wrote:
    John Larkin wrote:

    <snip>

    I guess one can plug an ssd into a PCIe slot.

    Worked for me. Didn't make spice run any faster, but it did make mousing round in the stored waveforms much faster.

    I need new PCs and it would be cool to have a fast D: drive on them, mostly for Dropbox.

    --
    Bill Sloman, Sydney

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Jan Panteltje@21:1/5 to jlarkin@highlandsniptechnology.com on Thu Jun 2 17:23:13 2022
    On a sunny day (Thu, 02 Jun 2022 06:33:32 -0700) it happened jlarkin@highlandsniptechnology.com wrote in <5pdh9htc6l399o9esj9ua3t9p145kd0vmo@4ax.com>:

    On Thu, 02 Jun 2022 06:05:25 GMT, Jan Panteltje
    <pNaonStpealmtje@yahoo.com> wrote:

    I know I probably draw fire if I say that all that spice is a dead end road at least for many things.

    It's sure not dead for people who design real electronics. What I want
    is for Spice to run on an Nvidia parallel compute engine, 200x or so
    faster than on an Intel cpu.


    Neural networks, done some programming with that, we are like that.. could be the future
    in electronic design too.
    But a NN (Neural Net) is trained by building and testing things.

    Are NNs anything but an academic toy?

    Many new medicines have been designed by AI now,
    it is worth keeping up to date on science by reading sciencedaily.com
    But also technical things, like airplane wings, what not.
    How did I learn? From looking at circuits, building and trying those.
    Big advantage for me is that I had to do fast fault finding in very complex systems
    and also simpler ones, so have seen thousands of designs, and HAD to grasp how those worked
    to be able to fix those.
    So you get an idea of the latest state of the art and what works and what not (when it fails)
    This is exactly how AI is trained, say for object recognition for military - or diagnostics for medical applications.


    Even if you spice on a supper computah there is NO guarantee the circuit will even work in reality.

    Sometimes things work exactly as Spiced. Good engineers can usually
    expect when the sims aren't to be trusted.


    I play with Raspberry Pis these days.. Even those are very much unobtainable due to chip or other shortages..
    Would be nice to have LT spice running on ARM processors (maybe there is a port already?)
    There must be a break even point between AI an Spice type simulations for electronic design?
    Wonder how far that is away.

    There have been attempts to use computers to actually design circuits,
    or at least to optimize values in a given topology. They tended to be >ludicrous failures.

    It's strange that our brains, evolved to be hunter-gatherers, can
    design electronics.

    For the rest I leave the problem solving to my neural net, have not touched spice in years?
    It is nice for filters that need a lot of repeated math scribbling, but there are other filter design programs.
    Many things do not have a good spice model...

    That's the main hazard, not having dependable part models. That's a
    serious problem when using RF-type parts large-signal time domain.

    We finally finished our big laser modulator chassis. The
    amplifier/fiducial board got to rev C, and we avoided D by adding a >MiniCircuits SMA DC block in one of the cables. You can't sim this
    fast stuff; just guess and etch.

    https://www.dropbox.com/s/29ttap9urihhep1/T500_Top_Final.jpg?raw=1

    Looks neat, what's in that metal box on the right?


    We couldn't get LCD driver chips, but their eval boards are available,
    so we used eval boards.

    Yes, I have some eval boards, also lots of small boards from China for cheap. About triacs.. ever used an ACS108S? Third time one blew up in my Whirlpool washing machine
    Does not like spikes on the mains it seems, ordered 10 for 4 $ from ebay..
    Very strange if you look at the datasheet it wants a negative drive, so takes plus as ground sort of thing

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From John Doe@21:1/5 to bitrex on Thu Jun 2 18:41:19 2022
    bitrex <user@example.net> wrote:

    jlarkin@highlandsniptechnology.com wrote:
    John Doe wrote:
    John Larkin wrote:

    I'll need to get a new PC soon. People say that a screaming CPU and
    lots of ram and solid-state C drive would really speed things up.

    I have had NVMe drives for ages. Get good ones, like from Samsung.
    Spend more than you used to spend on hard drives, it's well worth it.
    Primary (and secondary) storage is not whizbang fun, but as IBM used
    to put it, it affects "throughput" more than anything else. NVMe is
    what I have always wanted.

    If you use a secondary drive, the transfer rate between two premium
    NVMe drives is OUTRAGEOUS. Transferring movies from your downloads
    folder to the secondary drive is quick. Making backups of Windows is
    also quick.

    I guess one can plug an ssd into a PCIe slot. I need new PCs and it
    would be cool to have a fast D: drive on them, mostly for Dropbox.

    The terminology "NVMe" is critical, and some are better than others.

    At one point, before buying a motherboard with 2 NVMe slots, I used a PCIe card, like that, for the additional NVMe drive.

    As long as you have one NVMe drive on the motherboard and a second NVMe on
    that PCIe card, file transfers are about as (blazing) fast as a motherboard with 2 NVMe slots, but only when you are in Windows. For something like restoring backups of Windows that might happen outside of Windows, that card doesn't provide the same benefit as 2 slots on the motherboard. Probably to
    do with drivers loaded when Windows boots.

    I just copied a 2.7 GB file from one Samsung NVMe drive to the other. It took less than two seconds. This is my PC's storage configuration. My NVMe drives are not state-of-the-art, but they were a HUGE leap, even a big leap over "SSD"...

    https://www.flickr.com/photos/27532210@N04/?

    There is an old picture of file transfer there too, but it's a little
    faster than that now.

    Cross-probing large .raw files even stored on an SSD is still slow cuz
    they use a compressed format, to make it snappy you have to first
    convert the data file:

    <https://ltwiki.org/LTspiceHelp/LTspiceHelp/Fast_Access_File_Format.htm>

    which is also slow. Or with your new machine you can buy a bunch of RAM
    say 32 or 64 gig and make half of it a RAM drive dedicated to sim data
    which also speeds up probing considerably.

    64 gig of DDR5 is about $500 and $250 for 64 gig of DDR4 on Amazon these days.

    Difficult to believe how out of touch with reality that opinion appears to
    be, on something this plainly technical. Or maybe I'm missing something in
    the translation.

    "Cross-probing"?
    Something to do with PCB design?
    :D

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From bitrex@21:1/5 to John Doe on Thu Jun 2 16:39:13 2022
    On 6/2/2022 2:41 PM, John Doe wrote:

    Cross-probing large .raw files even stored on an SSD is still slow cuz
    they use a compressed format, to make it snappy you have to first
    convert the data file:

    <https://ltwiki.org/LTspiceHelp/LTspiceHelp/Fast_Access_File_Format.htm>

    which is also slow. Or with your new machine you can buy a bunch of RAM
    say 32 or 64 gig and make half of it a RAM drive dedicated to sim data
    which also speeds up probing considerably.

    64 gig of DDR5 is about $500 and $250 for 64 gig of DDR4 on Amazon these
    days.

    Difficult to believe how out of touch with reality that opinion appears to be, on something this plainly technical. Or maybe I'm missing something in the translation.

    "Cross-probing"?
    Something to do with PCB design?
    :D


    "This makes cross probing large circuits with huge simulation data files interactive."

    It's the term the authors of the LTSpice wiki used themselves in the
    link you didn't read.

    It means "You click on the node in the schematic you want to see the
    simulation plot for, and then the data you want to see appears in the
    window that shows the plot, or vice versa by clicking alt + left on a
    label in the plot pane and it will highlight the associated node"

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From three_jeeps@21:1/5 to jla...@highlandsniptechnology.com on Thu Jun 2 13:51:14 2022
    On Thursday, June 2, 2022 at 9:34:02 AM UTC-4, jla...@highlandsniptechnology.com wrote:
    On Thu, 02 Jun 2022 06:05:25 GMT, Jan Panteltje
    <pNaonSt...@yahoo.com> wrote:

    On a sunny day (Wed, 01 Jun 2022 15:38:20 -0700) it happened John Larkin ><jlarkin@highland_atwork_technology.com> wrote in ><m2pf9hp44ssn7vu45...@4ax.com>:

    I'm waiting for a sim to run, so may as well whine. It's running at 12 >>PPM of real time.

    LT Spice lets you put the value of a part anywhere on the screen. I
    just spent an embarassing amount of time figuring out why my current >>limiter didn't work. It's a switching half-bridge with an output
    current sensor, and a pair of P+I opamps that sense positive and >>negative over-current and clamp the input demand signal appropriately.

    (The current limit will be in an FPGA, but I like to do an analog sim
    to get the dynamics close.)

    I have a couple of BVs as isolators between the PWM generator and the >>floating (+ and - 48 volt supplies) LTC4444 mosfet gate driver. The >>equations of the BVs were swapped, so my power stage gain was
    reversed. Negative feedback wasn't.

    Some cad software limits how far a ref designator or a value can be
    from the part. Or highlights one if you click on the other.

    More fun: if you copy and paste a chunk of circuit, the copy has all
    the same node names. So everything is shorted to everything until you >>find and change the nodes that matter.

    I'll need to get a new PC soon. People say that a screaming CPU and
    lots of ram and solid-state C drive would really speed things up.

    Hey, it finished. It made a 5.4 Gbyte RAW file.

    There was a headline in scidaily.com today about if AI designed stuff should be patented and by whom, or something

    I know I probably draw fire if I say that all that spice is a dead end road at least for many things.
    It's sure not dead for people who design real electronics. What I want
    is for Spice to run on an Nvidia parallel compute engine, 200x or so
    faster than on an Intel cpu.

    Neural networks, done some programming with that, we are like that.. could be the future
    in electronic design too.
    But a NN (Neural Net) is trained by building and testing things.
    Are NNs anything but an academic toy?
    Even if you spice on a supper computah there is NO guarantee the circuit will even work in reality.
    Sometimes things work exactly as Spiced. Good engineers can usually
    expect when the sims aren't to be trusted.

    I play with Raspberry Pis these days.. Even those are very much unobtainable due to chip or other shortages..
    Would be nice to have LT spice running on ARM processors (maybe there is a port already?)
    There must be a break even point between AI an Spice type simulations for electronic design?
    Wonder how far that is away.
    There have been attempts to use computers to actually design circuits,
    or at least to optimize values in a given topology. They tended to be ludicrous failures.

    It's strange that our brains, evolved to be hunter-gatherers, can
    design electronics.
    For the rest I leave the problem solving to my neural net, have not touched spice in years?
    It is nice for filters that need a lot of repeated math scribbling, but there are other filter design programs.
    Many things do not have a good spice model...
    That's the main hazard, not having dependable part models. That's a
    serious problem when using RF-type parts large-signal time domain.

    We finally finished our big laser modulator chassis. The
    amplifier/fiducial board got to rev C, and we avoided D by adding a MiniCircuits SMA DC block in one of the cables. You can't sim this
    fast stuff; just guess and etch.

    https://www.dropbox.com/s/29ttap9urihhep1/T500_Top_Final.jpg?raw=1

    We couldn't get LCD driver chips, but their eval boards are available,
    so we used eval boards.



    --

    Anybody can count to one.

    - Robert Widlar

    * NN anything more than an academic toy?
    Ummm, they are integral computational entities in many products that require object detection, and pattern recognition. Many autonomous vehicles use them. I have worked on various airborne threat detection systems that have ANN classifiers.

    I developed ANN (Artificial Neural Net) based object detection and signal processing back in the early to mid 1990s. One application that I can talk about is object detection and classification in airline luggage. The quality of the ANN was and still
    is directly related to the number of training sets you throw at it. Coming up with sufficient number of training sets was a challenge. Fast forward 10 years and the explosion of the web - images by the gazillions.
    They are more mainstream than you can imagine.
    J

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Chris Jones@21:1/5 to jlarkin@highlandsniptechnology.com on Fri Jun 3 21:45:04 2022
    On 02/06/2022 23:33, jlarkin@highlandsniptechnology.com wrote:
    There have been attempts to use computers to actually design circuits,
    or at least to optimize values in a given topology. They tended to be ludicrous failures.

    I used an optimizer for some chip designs, it was very very good for
    things like choosing the size of the transistors in flipflops for best
    toggle frequency per supply current, and optimising a low pass filter
    for best noise and in-band error-vector-magnitude and stop-band
    rejection etc. all at the same time. It did way better than I could
    have. The trick was to write a script that runs the right simulations
    and results in an expression (or several) that correctly describes how
    well a circuit meets the goals. Once you've done that, it can twiddle
    the knobs much better than any human, and I don't mean because it could
    do it faster and spam the simulations across a thousand CPUs whilst you
    could look at only one at a time, it was also better in that it could
    remember many sets of parameters that were good in various ways, and
    combine them more efficiently than a human. It was a company internal
    tool and they will surely have kept it that way.

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Phil Hobbs@21:1/5 to Chris Jones on Fri Jun 3 10:30:51 2022
    Chris Jones wrote:
    On 02/06/2022 23:33, jlarkin@highlandsniptechnology.com wrote:
    There have been attempts to use computers to actually design
    circuits, or at least to optimize values in a given topology. They
    tended to be ludicrous failures.

    I used an optimizer for some chip designs, it was very very good for
    things like choosing the size of the transistors in flipflops for
    best toggle frequency per supply current, and optimising a low pass
    filter for best noise and in-band error-vector-magnitude and
    stop-band rejection etc. all at the same time. It did way better than
    I could have.

    Sounds like a super useful tool. I did something similar for optimizing plasmonic nanoantennas 15 or so years ago, and like yours, it found good solutions that weren't at all obvious. So I'm a fan of the general
    approach.

    Of course, that sort of thing has been done automatically since the
    1940s (or earlier, using manual methods--see e.g. <https://en.wikipedia.org/wiki/Linear_programming#History>.

    The trick was to write a script that runs the right simulations and
    results in an expression (or several) that correctly describes how
    well a circuit meets the goals. Once you've done that, it can twiddle
    the knobs much better than any human, and I don't mean because it
    could do it faster and spam the simulations across a thousand CPUs
    whilst you could look at only one at a time, it was also better in
    that it could remember many sets of parameters that were good in
    various ways, and combine them more efficiently than a human. It was
    a company internal tool and they will surely have kept it that way.

    Numerical optimization based on merit / penalty functions has been well
    known for 200 years, since Gauss iirc. That's a far cry from actual computer-based design.

    Even lenses, which you'd think would be a natural application, have been resistant to fully-automated design--it's all about finding a suitable
    starting point.

    There are various approaches that modify topologies, of which the best
    known are genetic algorithms.

    Cheers

    Phil Hobbs

    --
    Dr Philip C D Hobbs
    Principal Consultant
    ElectroOptical Innovations LLC / Hobbs ElectroOptics
    Optics, Electro-optics, Photonics, Analog Electronics
    Briarcliff Manor NY 10510

    http://electrooptical.net
    http://hobbs-eo.com

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Joe Gwinn@21:1/5 to pcdhSpamMeSenseless@electrooptical. on Fri Jun 3 11:38:29 2022
    On Fri, 3 Jun 2022 10:30:51 -0400, Phil Hobbs <pcdhSpamMeSenseless@electrooptical.net> wrote:

    Chris Jones wrote:
    On 02/06/2022 23:33, jlarkin@highlandsniptechnology.com wrote:
    There have been attempts to use computers to actually design
    circuits, or at least to optimize values in a given topology. They
    tended to be ludicrous failures.

    I used an optimizer for some chip designs, it was very very good for
    things like choosing the size of the transistors in flipflops for
    best toggle frequency per supply current, and optimising a low pass
    filter for best noise and in-band error-vector-magnitude and
    stop-band rejection etc. all at the same time. It did way better than
    I could have.

    Sounds like a super useful tool. I did something similar for optimizing >plasmonic nanoantennas 15 or so years ago, and like yours, it found good >solutions that weren't at all obvious. So I'm a fan of the general
    approach.

    Of course, that sort of thing has been done automatically since the
    1940s (or earlier, using manual methods--see e.g. ><https://en.wikipedia.org/wiki/Linear_programming#History>.

    The trick was to write a script that runs the right simulations and
    results in an expression (or several) that correctly describes how
    well a circuit meets the goals. Once you've done that, it can twiddle
    the knobs much better than any human, and I don't mean because it
    could do it faster and spam the simulations across a thousand CPUs
    whilst you could look at only one at a time, it was also better in
    that it could remember many sets of parameters that were good in
    various ways, and combine them more efficiently than a human. It was
    a company internal tool and they will surely have kept it that way.

    Numerical optimization based on merit / penalty functions has been well
    known for 200 years, since Gauss iirc. That's a far cry from actual >computer-based design.

    Even lenses, which you'd think would be a natural application, have been >resistant to fully-automated design--it's all about finding a suitable >starting point.

    There are various approaches that modify topologies, of which the best
    known are genetic algorithms.

    Yes. The part about " it could remember many sets of parameters that
    were good in various ways, and combine them more efficiently than a
    human" sounds very much like a genetic programming algorithm, which
    are very good at improving from a valid starting point.

    Joe Gwinn

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Phil Hobbs@21:1/5 to Joe Gwinn on Fri Jun 3 12:12:00 2022
    Joe Gwinn wrote:
    On Fri, 3 Jun 2022 10:30:51 -0400, Phil Hobbs <pcdhSpamMeSenseless@electrooptical.net> wrote:

    Chris Jones wrote:
    On 02/06/2022 23:33, jlarkin@highlandsniptechnology.com wrote:
    There have been attempts to use computers to actually design
    circuits, or at least to optimize values in a given topology. They
    tended to be ludicrous failures.

    I used an optimizer for some chip designs, it was very very good for
    things like choosing the size of the transistors in flipflops for
    best toggle frequency per supply current, and optimising a low pass
    filter for best noise and in-band error-vector-magnitude and
    stop-band rejection etc. all at the same time. It did way better than
    I could have.

    Sounds like a super useful tool. I did something similar for optimizing
    plasmonic nanoantennas 15 or so years ago, and like yours, it found good
    solutions that weren't at all obvious. So I'm a fan of the general
    approach.

    Of course, that sort of thing has been done automatically since the
    1940s (or earlier, using manual methods--see e.g.
    <https://en.wikipedia.org/wiki/Linear_programming#History>.

    The trick was to write a script that runs the right simulations and
    results in an expression (or several) that correctly describes how
    well a circuit meets the goals. Once you've done that, it can twiddle
    the knobs much better than any human, and I don't mean because it
    could do it faster and spam the simulations across a thousand CPUs
    whilst you could look at only one at a time, it was also better in
    that it could remember many sets of parameters that were good in
    various ways, and combine them more efficiently than a human. It was
    a company internal tool and they will surely have kept it that way.

    Numerical optimization based on merit / penalty functions has been well
    known for 200 years, since Gauss iirc. That's a far cry from actual
    computer-based design.

    Even lenses, which you'd think would be a natural application, have been
    resistant to fully-automated design--it's all about finding a suitable
    starting point.

    There are various approaches that modify topologies, of which the best
    known are genetic algorithms.

    Yes. The part about " it could remember many sets of parameters that
    were good in various ways, and combine them more efficiently than a
    human" sounds very much like a genetic programming algorithm, which
    are very good at improving from a valid starting point.

    Joe Gwinn


    Not as far as I know. The point of genetic algos is to change the
    topology, not just the values. Unless I'm misunderstanding, Chris's
    optimizer was the usual sort that tweaks parameters to minimize some
    penalty function. Most of those remember previous values too--for
    instance my usual go-to algo, the Nelder-Mead downhill simplex method ('amoeba()' in Numerical Recipes). For N variables, it keeps N+1 sets.

    I like Nelder-Mead because most of the things I need to optimize are
    either discontinuous themselves, like the number and placement of
    rectangular boxes of metal in a nanoantenna, or else need to be
    constrained to physically realizable values, as in a filter design code
    where the component values need to be positive. (I usually use
    mirroring to constrain that sort of thing, which avoids the tendency of
    the simplex to collapse along the discontinuity like water along a curb.)

    Cheers

    Phil Hobbs

    --
    Dr Philip C D Hobbs
    Principal Consultant
    ElectroOptical Innovations LLC / Hobbs ElectroOptics
    Optics, Electro-optics, Photonics, Analog Electronics
    Briarcliff Manor NY 10510

    http://electrooptical.net
    http://hobbs-eo.com

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Clifford Heath@21:1/5 to Joe Gwinn on Sat Jun 4 09:01:18 2022
    On 4/6/22 01:38, Joe Gwinn wrote:
    On Fri, 3 Jun 2022 10:30:51 -0400, Phil Hobbs <pcdhSpamMeSenseless@electrooptical.net> wrote:

    Chris Jones wrote:
    On 02/06/2022 23:33, jlarkin@highlandsniptechnology.com wrote:
    There have been attempts to use computers to actually design
    circuits, or at least to optimize values in a given topology. They
    tended to be ludicrous failures.

    I used an optimizer for some chip designs, it was very very good for
    things like choosing the size of the transistors in flipflops for
    best toggle frequency per supply current, and optimising a low pass
    filter for best noise and in-band error-vector-magnitude and
    stop-band rejection etc. all at the same time. It did way better than
    I could have.

    Sounds like a super useful tool. I did something similar for optimizing
    plasmonic nanoantennas 15 or so years ago, and like yours, it found good
    solutions that weren't at all obvious. So I'm a fan of the general
    approach.

    Of course, that sort of thing has been done automatically since the
    1940s (or earlier, using manual methods--see e.g.
    <https://en.wikipedia.org/wiki/Linear_programming#History>.

    The trick was to write a script that runs the right simulations and
    results in an expression (or several) that correctly describes how
    well a circuit meets the goals. Once you've done that, it can twiddle
    the knobs much better than any human, and I don't mean because it
    could do it faster and spam the simulations across a thousand CPUs
    whilst you could look at only one at a time, it was also better in
    that it could remember many sets of parameters that were good in
    various ways, and combine them more efficiently than a human. It was
    a company internal tool and they will surely have kept it that way.

    Numerical optimization based on merit / penalty functions has been well
    known for 200 years, since Gauss iirc. That's a far cry from actual
    computer-based design.

    Even lenses, which you'd think would be a natural application, have been
    resistant to fully-automated design--it's all about finding a suitable
    starting point.

    There are various approaches that modify topologies, of which the best
    known are genetic algorithms.

    Yes. The part about " it could remember many sets of parameters that
    were good in various ways, and combine them more efficiently than a
    human" sounds very much like a genetic programming algorithm, which
    are very good at improving from a valid starting point.

    It sounds like multi-dimensional slope-descent to me.

    These are very good at finding local optima for a given design. Design
    from scratch requires finding global optima, something that
    slope-descent isn't very good at. Simulated annealing and genetic
    programming might have more luck.

    CH

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Anthony William Sloman@21:1/5 to Clifford Heath on Fri Jun 3 22:41:03 2022
    On Saturday, June 4, 2022 at 9:02:09 AM UTC+10, Clifford Heath wrote:
    On 4/6/22 01:38, Joe Gwinn wrote:
    On Fri, 3 Jun 2022 10:30:51 -0400, Phil Hobbs <pcdhSpamM...@electrooptical.net> wrote:
    Chris Jones wrote:
    On 02/06/2022 23:33, jla...@highlandsniptechnology.com wrote:

    <snip>

    Yes. The part about " it could remember many sets of parameters that
    were good in various ways, and combine them more efficiently than a
    human" sounds very much like a genetic programming algorithm, which
    are very good at improving from a valid starting point.

    It sounds like multi-dimensional slope-descent to me.

    I actually used non-linear multi-parameter curve fitting in my Ph.D. work back around 1968. It did rely on a finite continuous data to create the surface that it crawled across. I used the Fletcher-Powell algorithm rather than Marquardt, but there are
    plenty of others.

    https://www.sciencedirect.com/science/article/abs/pii/0167715283900494

    These are very good at finding local optima for a given design. Design
    from scratch requires finding global optima, something that
    slope-descent isn't very good at. Simulated annealing and genetic programming might have more luck.

    That does sound right.

    --
    Bill Sloman, Sydney

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From legg@21:1/5 to pcdhSpamMeSenseless@electrooptical. on Sat Jun 4 07:54:31 2022
    On Fri, 3 Jun 2022 10:30:51 -0400, Phil Hobbs <pcdhSpamMeSenseless@electrooptical.net> wrote:

    Chris Jones wrote:
    On 02/06/2022 23:33, jlarkin@highlandsniptechnology.com wrote:
    There have been attempts to use computers to actually design
    circuits, or at least to optimize values in a given topology. They
    tended to be ludicrous failures.

    I used an optimizer for some chip designs, it was very very good for
    things like choosing the size of the transistors in flipflops for
    best toggle frequency per supply current, and optimising a low pass
    filter for best noise and in-band error-vector-magnitude and
    stop-band rejection etc. all at the same time. It did way better than
    I could have.

    Sounds like a super useful tool. I did something similar for optimizing >plasmonic nanoantennas 15 or so years ago, and like yours, it found good >solutions that weren't at all obvious. So I'm a fan of the general
    approach.

    Of course, that sort of thing has been done automatically since the
    1940s (or earlier, using manual methods--see e.g. ><https://en.wikipedia.org/wiki/Linear_programming#History>.

    The trick was to write a script that runs the right simulations and
    results in an expression (or several) that correctly describes how
    well a circuit meets the goals. Once you've done that, it can twiddle
    the knobs much better than any human, and I don't mean because it
    could do it faster and spam the simulations across a thousand CPUs
    whilst you could look at only one at a time, it was also better in
    that it could remember many sets of parameters that were good in
    various ways, and combine them more efficiently than a human. It was
    a company internal tool and they will surely have kept it that way.

    Numerical optimization based on merit / penalty functions has been well
    known for 200 years, since Gauss iirc. That's a far cry from actual >computer-based design.

    Even lenses, which you'd think would be a natural application, have been >resistant to fully-automated design--it's all about finding a suitable >starting point.

    There are various approaches that modify topologies, of which the best
    known are genetic algorithms.

    Cheers

    Phil Hobbs

    You can do the same thing with a list of components to generate a
    simple figure of merit for an application. Can include such esoteric
    issues as cost (book, real estate, process).

    Don't stock market analysis programs try to do this in real time?
    Muddying their own pool . . . . .

    RL

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Martin Brown@21:1/5 to Phil Hobbs on Sat Jun 4 14:07:56 2022
    On 03/06/2022 15:30, Phil Hobbs wrote:
    Chris Jones wrote:
    On 02/06/2022 23:33, jlarkin@highlandsniptechnology.com wrote:
    There have been attempts to use computers to actually design
    circuits, or at least to optimize values in a given topology. They
     tended to be ludicrous failures.

    I used an optimizer for some chip designs, it was very very good for
     things like choosing the size of the transistors in flipflops for
    best toggle frequency per supply current, and optimising a low pass
    filter for best noise and in-band error-vector-magnitude and stop-band
    rejection etc. all at the same time. It did way better than
    I could have.

    Sounds like a super useful tool.  I did something similar for optimizing plasmonic nanoantennas 15 or so years ago, and like yours, it found good solutions that weren't at all obvious.  So I'm a fan of the general approach.

    Simulated annealing or simplex are pretty good for that sort of thing.
    Then conjugate gradients once you get somewhere near an optimum.

    You may never be sure you have the global optimum but it will probably
    find a solution that is better than any human can in a reasonable time.

    The trick was to write a script that runs the right simulations and
    results in an expression (or several) that correctly describes how
    well a circuit meets the goals. Once you've done that, it can twiddle
    the knobs much better than any human, and I don't mean because it
    could do it faster and spam the simulations across a thousand CPUs
    whilst you could look at only one at a time, it was also better in
    that it could remember many sets of parameters that were good in
    various ways, and combine them more efficiently than a human. It was
    a company internal tool and they will surely have kept it that way.

    Numerical optimization based on merit / penalty functions has been well
    known for 200 years, since Gauss iirc.  That's a far cry from actual computer-based design.

    Even lenses, which you'd think would be a natural application, have been resistant to fully-automated design--it's all about finding a suitable starting point.

    Optical lens designs have been pretty much solved now at least in the
    domains that I frequent. There could only be a handful of truly weird configurations remaining that haven't been tried already.

    The last interesting one in terms of being very different to orthodoxy
    was Willstrop's three mirror telescope (no chromatic or sphereical
    aberration, precise focus and very fast).

    https://www.ast.cam.ac.uk/about/three-mirror.telescope

    To the best of my knowledge no full scale one has ever been built.

    I expect the odd novelty still lurks in the shadows. The search for
    eyepieces with ever more wide angle views remains the Holy grail - they
    are getting a bit ridiculous now with some offering 120 degree AFOV.

    https://www.telescopehouse.com/Telescope-Accessories/EXPLORE-SCIENTIFIC-120-Ar-Eyepiece-9mm-2.html

    I think that is the current record holder but I could be wrong on that.
    Price and weight are both a bit on the high side (lots of glass in it).

    There are various approaches that modify topologies, of which the best
    known are genetic algorithms.

    Modifying the topology is best done by humans. Optimising the components against some library of available materials and shapes is now the domain
    of sophisticated ray tracing programs. Zemax is probably the best known:

    https://www.zemax.com/pages/try-opticstudio-for-free

    Learning curve could best be described as STEEP...

    --
    Regards,
    Martin Brown

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From Phil Hobbs@21:1/5 to legg on Sat Jun 4 08:57:33 2022
    legg wrote:
    On Fri, 3 Jun 2022 10:30:51 -0400, Phil Hobbs <pcdhSpamMeSenseless@electrooptical.net> wrote:

    Chris Jones wrote:
    On 02/06/2022 23:33, jlarkin@highlandsniptechnology.com wrote:
    There have been attempts to use computers to actually design
    circuits, or at least to optimize values in a given topology. They
    tended to be ludicrous failures.

    I used an optimizer for some chip designs, it was very very good for
    things like choosing the size of the transistors in flipflops for
    best toggle frequency per supply current, and optimising a low pass
    filter for best noise and in-band error-vector-magnitude and
    stop-band rejection etc. all at the same time. It did way better than
    I could have.

    Sounds like a super useful tool. I did something similar for optimizing
    plasmonic nanoantennas 15 or so years ago, and like yours, it found good
    solutions that weren't at all obvious. So I'm a fan of the general
    approach.

    Of course, that sort of thing has been done automatically since the
    1940s (or earlier, using manual methods--see e.g.
    <https://en.wikipedia.org/wiki/Linear_programming#History>.

    The trick was to write a script that runs the right simulations and
    results in an expression (or several) that correctly describes how
    well a circuit meets the goals. Once you've done that, it can twiddle
    the knobs much better than any human, and I don't mean because it
    could do it faster and spam the simulations across a thousand CPUs
    whilst you could look at only one at a time, it was also better in
    that it could remember many sets of parameters that were good in
    various ways, and combine them more efficiently than a human. It was
    a company internal tool and they will surely have kept it that way.

    Numerical optimization based on merit / penalty functions has been well
    known for 200 years, since Gauss iirc. That's a far cry from actual
    computer-based design.

    Even lenses, which you'd think would be a natural application, have been
    resistant to fully-automated design--it's all about finding a suitable
    starting point.

    There are various approaches that modify topologies, of which the best
    known are genetic algorithms.


    You can do the same thing with a list of components to generate a
    simple figure of merit for an application. Can include such esoteric
    issues as cost (book, real estate, process).


    Sure. My EM simulator can optimize on literally anything expressible in
    its input files.

    The issue isn't figuring out how good a design is, it's generating good
    ones from a blank sheet of paper.

    Cheers

    Phil Hobbs

    --
    Dr Philip C D Hobbs
    Principal Consultant
    ElectroOptical Innovations LLC / Hobbs ElectroOptics
    Optics, Electro-optics, Photonics, Analog Electronics
    Briarcliff Manor NY 10510

    http://electrooptical.net
    http://hobbs-eo.com

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From John Doe@21:1/5 to John Doe on Sun Jun 12 20:57:59 2022
    Samsung 980 Pro NVMe SSD 1TB PCIe 4.0 (Amazon)

    Oom, baby.

    The 2 TB version jumps to $270. But if money is no object, those two would
    make an amazing primary and secondary drive combination. Primary being
    smaller.

    I'm only using half of my 960 Pro (primary drive) and I already have the 980 original (secondary drive).









    John Doe <always.look@message.header> wrote:

    John Larkin wrote:

    I'll need to get a new PC soon. People say that a screaming CPU and lots
    of ram and solid-state C drive would really speed things up.

    I have had NVMe drives for ages. Get good ones, like from Samsung. Spend
    more than you used to spend on hard drives, it's well worth it. Primary
    (and secondary) storage is not whizbang fun, but as IBM used to put it, it affects "throughput" more than anything else. NVMe is what I have always wanted.

    If you use a secondary drive, the transfer rate between two premium NVMe drives is OUTRAGEOUS. Transferring movies from your downloads folder to
    the secondary drive is quick. Making backups of Windows is also quick.

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)
  • From John Doe@21:1/5 to All on Sun Jun 12 20:59:07 2022
    The 1 TB is $155. Great price.

    --- SoupGate-Win32 v1.05
    * Origin: fsxNet Usenet Gateway (21:1/5)