02/02/2025 - 08/02/2025
03/02/2025 15:33
Meeting with Marcus 01/31/2025
UDP Packet format:
- Each channel sends it's own "event fragment" with it's own timestamp
- Need to listen for event fragments with some collector logic before parsing into a full event
- Supposedly once an event is "collected," the parser in the naludaq package should work (though Marcus mentioned it will be slow)
Rate Limitations:
- The board has a parallel bus limited to 31.5MHz, samples are 12 bits long so the amount of real data we can get out is ~50MB/s (maybe header/trailer caused a bump so we could see 55MB/s)
- There is some firmware issue for event creation at higher rates that causes a performance drop when the system is overwhelmed (~20kHz or 100000 packages(?))
Sampling rate:
- To move from 1Gsps to ~1.6Gsps is "tricky" according to marcus, but can be done on the HDSoCv1. He made it sound like it will be less of an issue on newer versions
Using the Threshold Scanner:
- The threshold scanner "tool" in the naludaq package should just "work"
- Marcus mentioned the trigger values are very stable
- But we will need to compute them anytime we adjust the internal trigger in any way at the very least.
Documentation:
- Marcus mentioned he'd send an updated naludaq documentation, ~ v0.30
03/02/2025 15:34
Here is the table image transcribed
12-bit data format, RAW readout from ASIC
| 2nd 1 Byte1 [15..8] | 1st 1 Byte1 [7..0] |
|---|---|
| 0xE0 | channel number [7..0] |
| 0xE[15..12] & trigger arrival time 1 [11..8] | trigger arrival time 1 [7..0] |
| 0xE[15..12] & trigger arrival time 2 [11..8] | trigger arrival time 2 [7..0] |
| 0xE[15..12] & logical position [11..8] | logical position [7..6] & physical position [5..0] |
| sample 1 data [15..8] | sample 1 data [7..4] & sample 2 data [3..0] |
| sample 2 data [15..8] | sample 3 data [7..0] |
| sample 3 data [15..12] & sample 4 data [11..8] | sample 4 data [7..0] |
| ... | ... |
| sample 31 data [15..12] & sample 32 data [11..8] | sample 32 data [7..0] |
| 0x0A | 0x5A |
| CRC | packet footer |
| ... | ... |
| 0xE0 | channel number [7..0] |
| 0xE[15..12] & trigger arrival time 1 [11..8] | trigger arrival time 1 [7..0] |
| 0xE[15..12] & trigger arrival time 2 [11..8] | trigger arrival time 2 [7..0] |
| 0xE[15..12] & logical position [11..8] | logical position [7..6] & physical position [5..0] |
| sample 1 data [15..8] | sample 1 data [7..4] & sample 2 data [3..0] |
| sample 2 data [15..8] | sample 3 data [7..0] |
| sample 3 data [15..12] & sample 4 data [11..8] | sample 4 data [7..0] |
| ... | ... |
| sample 31 data [15..12] & sample 32 data [11..8] | sample 32 data [7..0] |
| 0x0A | 0x5A |
| CRC | packet footer |
16-bit "expanded" data, used in NaluDAQ
| 2nd 1 Byte1 [15..8] | 1st 1 Byte1 [7..0] |
|---|---|
| 0xE0 | channel number [7..0] |
| 0x0[15..12] & trigger arrival time 1 [11..8] | trigger arrival time 1 [7..0] |
| 0x0[15..12] & trigger arrival time 2 [11..8] | trigger arrival time 2 [7..0] |
| 0x0[15..12] & logical position [11..8] | logical position [7..6] & physical position [5..0] |
| sample 1 data [11..8] | sample1 data [7..0] |
| sample 2 data [11..8] | sample2 data [7..0] |
| ... | ... |
| sample 32 data [11..8] | sample 32 data [7..0] |
| 0x0A | 0x5A |
| 0xFE | 0xCA |
| ... | ... |
| 0xE0 | channel number [7..0] |
| 0x0[15..12] & trigger arrival time 1 [11..8] | trigger arrival time 1 [7..0] |
| 0x0[15..12] & trigger arrival time 2 [11..8] | trigger arrival time 2 [7..0] |
| 0x0[15..12] & logical position [11..8] | logical position [7..6] & physical position [5..0] |
| sample 1 data [11..8] | sample1 data [7..0] |
| sample 2 data [11..8] | sample2 data [7..0] |
| ... | ... |
| sample 32 data [11..8] | sample 32 data [7..0] |
| 0x0A | 0x5A |
| 0xFE | 0xCA |
03/02/2025 15:47
I was able to get a conda environment to have root and some machine learning libraries at the same time. It took a few attempts because there's some nuance. First off, the ML libraries are a few versions of python behind, so I had to use python 3.10 (as oppose to 3.12). Second, I had to use the correct keywords when building the environment:
conda create --name root_env -c conda-forge -c root python=3.10 cudatoolkit=11.8 numpy matplotlib scikit-learn pytorch=2.1 torchvision tensorflow jupyter
conda create --name root_env -c conda-forge -c root python=3.10 cudatoolkit=11.8 numpy matplotlib scikit-learn pytorch=2.1 torchvision tensorflow jupyterROOT seemed to not want to install, so I tried it again
conda install -c conda-forge root
conda install -c conda-forge rootand it seemed to install on the second pass. This notably doesn't include torch audio, if that's needed.
Afterwards you can test some of the installations:
python -c "import torch; print(torch.cuda.is_available())" python -c "import tensorflow as tf; print(tf.__version__)" python -c "import sklearn; print(sklearn.__version__)" python -c "import ROOT; print(ROOT.__version__)
python -c "import torch; print(torch.cuda.is_available())"
python -c "import tensorflow as tf; print(tf.__version__)"
python -c "import sklearn; print(sklearn.__version__)"
python -c "import ROOT; print(ROOT.__version__)03/02/2025 16:52
Judging by this plot, I'm pretty sure we're in the 16-bit "expanded" data because I see 8 bytes, then data, then a footer byte (0xFA5A). This footer byte does not match the image Marcus sent us but does match the input parameters to the HDSoC class:
class HDSoCParser(Parser):
def __init__(self, params):
super().__init__(params)
self._stop_word = params.get("stop_word", b"\xfa\x5a")
if isinstance(self._stop_word, str):
self._stop_word = bytes.fromhex(self._stop_word)
self._chan_mask = params.get("chanmask", 0x3F)
self._chan_shift = params.get("chanshift", 0)
self._abs_wind_mask = params.get("abs_wind_mask", 0x3F)
self._evt_wind_mask = params.get("evt_wind_mask", 0x3F)
self._evt_wind_shift = params.get("evt_wind_shift", 6)
self._headers = params.get("headers", 4)
self._timing_mask = params.get("timing_mask", 0xFFF)
self._timing_shift = params.get("timing_mask", 12)
self._packet_size = 72class HDSoCParser(Parser):
def __init__(self, params):
super().__init__(params)
self._stop_word = params.get("stop_word", b"\xfa\x5a")
if isinstance(self._stop_word, str):
self._stop_word = bytes.fromhex(self._stop_word)
self._chan_mask = params.get("chanmask", 0x3F)
self._chan_shift = params.get("chanshift", 0)
self._abs_wind_mask = params.get("abs_wind_mask", 0x3F)
self._evt_wind_mask = params.get("evt_wind_mask", 0x3F)
self._evt_wind_shift = params.get("evt_wind_shift", 6)
self._headers = params.get("headers", 4)
self._timing_mask = params.get("timing_mask", 0xFFF)
self._timing_shift = params.get("timing_mask", 12)
self._packet_size = 7203/02/2025 18:40
I had to fill in some blanks, but I think I was able to correctly reconstruct the channel, time, and samples of a 1040 byte UDP package (not really sure what logical and physical position are):
{'Channel': 0, 'Trigger Time': 16031077, 'Logical Position': 0, 'Physical Position': 29, 'Samples': [1496, 1511, 1503, 1515, 1474, 1489, 1492, 1470, 1488, 1490, 1486, 1467, 1464, 1466, 1480, 1494, 1464, 1506, 1497, 1485, 1489, 1489, 1496, 1516, 1508, 1444, 1482, 1464, 1494, 1486, 1489, 1559], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16032109, 'Logical Position': 0, 'Physical Position': 7, 'Samples': [1489, 1498, 1504, 1514, 1488, 1497, 1490, 1488, 1492, 1508, 1468, 1490, 1491, 1471, 1480, 1461, 1467, 1496, 1512, 1498, 1468, 1461, 1505, 1500, 1492, 1487, 1520, 1494, 1504, 1495, 1494, 1518], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16033142, 'Logical Position': 0, 'Physical Position': 48, 'Samples': [1509, 1455, 1442, 1519, 1528, 1481, 1515, 1494, 1506, 1497, 1480, 1494, 1464, 1477, 1489, 1483, 1509, 1511, 1491, 1484, 1494, 1488, 1441, 1468, 1472, 1494, 1474, 1466, 1467, 1486, 1527, 1493], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16034175, 'Logical Position': 0, 'Physical Position': 27, 'Samples': [1478, 1506, 1492, 1520, 1458, 1495, 1467, 1469, 1476, 1504, 1512, 1486, 1468, 1494, 1518, 1504, 1491, 1523, 1516, 1494, 1502, 1461, 1452, 1443, 1491, 1520, 1512, 1495, 1488, 1500, 1473, 1522], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16035207, 'Logical Position': 0, 'Physical Position': 5, 'Samples': [1503, 1490, 1445, 1512, 1491, 1491, 1496, 1496, 1443, 1505, 1514, 1502, 1483, 1442, 1496, 1490, 1490, 1494, 1502, 1512, 1503, 1488, 1508, 1491, 1490, 1499, 1485, 1454, 1458, 1474, 1486, 1511], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16037273, 'Logical Position': 0, 'Physical Position': 25, 'Samples': [1479, 1518, 1501, 1525, 1494, 1484, 1494, 1457, 1505, 1492, 1507, 1500, 1467, 1486, 1506, 1513, 1501, 1490, 1494, 1488, 1465, 1477, 1468, 1496, 1493, 1520, 1515, 1486, 1478, 1510, 1488, 1541], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16038305, 'Logical Position': 0, 'Physical Position': 3, 'Samples': [1468, 1467, 1507, 1541, 1503, 1508, 1516, 1477, 1492, 1470, 1524, 1512, 1504, 1496, 1499, 1517, 1465, 1505, 1499, 1471, 1480, 1495, 1496, 1517, 1498, 1518, 1464, 1466, 1503, 1492, 1493, 1544], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16039338, 'Logical Position': 0, 'Physical Position': 44, 'Samples': [1531, 1441, 1488, 1482, 1494, 1488, 1506, 1489, 1471, 1486, 1477, 1482, 1470, 1488, 1442, 1463, 1490, 1516, 1500, 1472, 1486, 1514, 1484, 1515, 1487, 1513, 1512, 1494, 1486, 1490, 1513, 1486], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16040371, 'Logical Position': 0, 'Physical Position': 23, 'Samples': [1510, 1486, 1510, 1522, 1486, 1488, 1493, 1457, 1475, 1492, 1539, 1508, 1491, 1470, 1551, 1518, 1504, 1512, 1492, 1468, 1481, 1490, 1499, 1512, 1500, 1490, 1515, 1499, 1516, 1513, 1468, 1552], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16042436, 'Logical Position': 0, 'Physical Position': 42, 'Samples': [1538, 1468, 1467, 1492, 1464, 1477, 1459, 1478, 1488, 1486, 1464, 1464, 1475, 1466, 1480, 1479, 1468, 1504, 1492, 1503, 1486, 1484, 1447, 1486, 1478, 1488, 1490, 1487, 1480, 1478, 1488, 1467], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16043469, 'Logical Position': 0, 'Physical Position': 21, 'Samples': [1502, 1476, 1481, 1517, 1449, 1460, 1465, 1469, 1468, 1502, 1508, 1492, 1464, 1506, 1510, 1495, 1478, 1512, 1504, 1530, 1478, 1477, 1480, 1496, 1473, 1497, 1491, 1487, 1462, 1484, 1462, 1494], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16044502, 'Logical Position': 0, 'Physical Position': 0, 'Samples': [1500, 1517, 1477, 1494, 1476, 1502, 1489, 1463, 1486, 1464, 1467, 1491, 1481, 1493, 1474, 1480, 1512, 1524, 1483, 1482, 1496, 1494, 1432, 1490, 1488, 1513, 1484, 1511, 1477, 1520, 1510, 1537], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16045535, 'Logical Position': 0, 'Physical Position': 41, 'Samples': [1483, 1497, 1470, 1494, 1440, 1485, 1488, 1494, 1459, 1458, 1493, 1486, 1496, 1495, 1499, 1510, 1486, 1493, 1507, 1469, 1487, 1478, 1517, 1489, 1498, 1494, 1488, 1508, 1474, 1511, 1470, 1490], 'Footer': (250, 90)}{'Channel': 0, 'Trigger Time': 16031077, 'Logical Position': 0, 'Physical Position': 29, 'Samples': [1496, 1511, 1503, 1515, 1474, 1489, 1492, 1470, 1488, 1490, 1486, 1467, 1464, 1466, 1480, 1494, 1464, 1506, 1497, 1485, 1489, 1489, 1496, 1516, 1508, 1444, 1482, 1464, 1494, 1486, 1489, 1559], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16032109, 'Logical Position': 0, 'Physical Position': 7, 'Samples': [1489, 1498, 1504, 1514, 1488, 1497, 1490, 1488, 1492, 1508, 1468, 1490, 1491, 1471, 1480, 1461, 1467, 1496, 1512, 1498, 1468, 1461, 1505, 1500, 1492, 1487, 1520, 1494, 1504, 1495, 1494, 1518], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16033142, 'Logical Position': 0, 'Physical Position': 48, 'Samples': [1509, 1455, 1442, 1519, 1528, 1481, 1515, 1494, 1506, 1497, 1480, 1494, 1464, 1477, 1489, 1483, 1509, 1511, 1491, 1484, 1494, 1488, 1441, 1468, 1472, 1494, 1474, 1466, 1467, 1486, 1527, 1493], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16034175, 'Logical Position': 0, 'Physical Position': 27, 'Samples': [1478, 1506, 1492, 1520, 1458, 1495, 1467, 1469, 1476, 1504, 1512, 1486, 1468, 1494, 1518, 1504, 1491, 1523, 1516, 1494, 1502, 1461, 1452, 1443, 1491, 1520, 1512, 1495, 1488, 1500, 1473, 1522], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16035207, 'Logical Position': 0, 'Physical Position': 5, 'Samples': [1503, 1490, 1445, 1512, 1491, 1491, 1496, 1496, 1443, 1505, 1514, 1502, 1483, 1442, 1496, 1490, 1490, 1494, 1502, 1512, 1503, 1488, 1508, 1491, 1490, 1499, 1485, 1454, 1458, 1474, 1486, 1511], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16037273, 'Logical Position': 0, 'Physical Position': 25, 'Samples': [1479, 1518, 1501, 1525, 1494, 1484, 1494, 1457, 1505, 1492, 1507, 1500, 1467, 1486, 1506, 1513, 1501, 1490, 1494, 1488, 1465, 1477, 1468, 1496, 1493, 1520, 1515, 1486, 1478, 1510, 1488, 1541], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16038305, 'Logical Position': 0, 'Physical Position': 3, 'Samples': [1468, 1467, 1507, 1541, 1503, 1508, 1516, 1477, 1492, 1470, 1524, 1512, 1504, 1496, 1499, 1517, 1465, 1505, 1499, 1471, 1480, 1495, 1496, 1517, 1498, 1518, 1464, 1466, 1503, 1492, 1493, 1544], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16039338, 'Logical Position': 0, 'Physical Position': 44, 'Samples': [1531, 1441, 1488, 1482, 1494, 1488, 1506, 1489, 1471, 1486, 1477, 1482, 1470, 1488, 1442, 1463, 1490, 1516, 1500, 1472, 1486, 1514, 1484, 1515, 1487, 1513, 1512, 1494, 1486, 1490, 1513, 1486], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16040371, 'Logical Position': 0, 'Physical Position': 23, 'Samples': [1510, 1486, 1510, 1522, 1486, 1488, 1493, 1457, 1475, 1492, 1539, 1508, 1491, 1470, 1551, 1518, 1504, 1512, 1492, 1468, 1481, 1490, 1499, 1512, 1500, 1490, 1515, 1499, 1516, 1513, 1468, 1552], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16042436, 'Logical Position': 0, 'Physical Position': 42, 'Samples': [1538, 1468, 1467, 1492, 1464, 1477, 1459, 1478, 1488, 1486, 1464, 1464, 1475, 1466, 1480, 1479, 1468, 1504, 1492, 1503, 1486, 1484, 1447, 1486, 1478, 1488, 1490, 1487, 1480, 1478, 1488, 1467], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16043469, 'Logical Position': 0, 'Physical Position': 21, 'Samples': [1502, 1476, 1481, 1517, 1449, 1460, 1465, 1469, 1468, 1502, 1508, 1492, 1464, 1506, 1510, 1495, 1478, 1512, 1504, 1530, 1478, 1477, 1480, 1496, 1473, 1497, 1491, 1487, 1462, 1484, 1462, 1494], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16044502, 'Logical Position': 0, 'Physical Position': 0, 'Samples': [1500, 1517, 1477, 1494, 1476, 1502, 1489, 1463, 1486, 1464, 1467, 1491, 1481, 1493, 1474, 1480, 1512, 1524, 1483, 1482, 1496, 1494, 1432, 1490, 1488, 1513, 1484, 1511, 1477, 1520, 1510, 1537], 'Footer': (250, 90)}
{'Channel': 0, 'Trigger Time': 16045535, 'Logical Position': 0, 'Physical Position': 41, 'Samples': [1483, 1497, 1470, 1494, 1440, 1485, 1488, 1494, 1459, 1458, 1493, 1486, 1496, 1495, 1499, 1510, 1486, 1493, 1507, 1469, 1487, 1478, 1517, 1489, 1498, 1494, 1488, 1508, 1474, 1511, 1470, 1490], 'Footer': (250, 90)}this looks very similar to the data I got from NaluScopes acquistions:
{'window_labels': [[], [], [32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43,
44, 45, 46, 47], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [],
[], [], [], [], [], [], [], [], [], [], [], [], [], []],
'evt_window_labels': [[], [], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [],
[], [], [], [], [], [], [], [], [], [], []], 'data': [array([],
dtype=float64), array([], dtype=float64), array([2053, 2108, 2102, 2078,
2073, 2092, 2099, 2090, 2058, 2074, 2076,
2095, 2094, 2078, 2028, 2069, 2106, 2088, 2072, 2025, 2009, 2082,
2078, 2067, 2068, 2058, 2028, 2054, 2024, 2075, 2074, 2080, 2056,
2046, 2071, 2076, 2054, 2044, 2078, 2085, 2002, 2032, 2040, 2035,
2033, 2046, 2050, 2025, 2033, 2078, 2071, 2040, 2005, 2026, 2044,
2040, 2003, 2040, 2046, 2032, 2055, 2076, 2054, 2025, 2040, 2069,
2082, 2088, 2048, 2046, 2052, 1984, 1664, 1573, 1573, 1620, 1572,
1558, 1529, 1518, 1534, 1541, 1538, 1480, 1491, 1516, 1520, 1477,
1529, 1519, 1459, 1488, 1486, 1500, 1517, 1516, 1590, 1516, 1566,
1554, 1518, 1517, 1528, 1516, 1455, 1446, 1486, 1466, 1488, 1468,
1467, 1452, 1486, 1467, 1510, 1526, 1463, 1492, 1487, 1451, 1491,
1506, 1468, 1491, 1496, 1516, 1493, 1481, 1487, 1493, 1492, 1490,
1470, 1469, 1484, 1502, 1495, ...
1627, 1623, 1618, 1645, 1595, 1614, 1622, 1667, 1606, 1620, 1648,
1619, 1669, 1614, 1640, 1655, 1616, 1638, 1602, 1642, 1625, 1618,
1667, 1621, 1618, 1646, 1624, 1646], dtype=uint16), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64)], 'timing': [[], [], [10488814, 10488814, 10488814,
10488814, 10488814, 10488814, 10488814, 10488814, 10488814, 10488814,
10488814, 10488814, 10488814, 10488814, 10488814, 10488814], [], [], [], [],
[], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [],
[], [], [], [], [], []], 'time': [array([], dtype=float64), array([],
dtype=float64), array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,
26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38,
39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,
52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64,
65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77,
78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103,
104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116,
117, 118, 119, 120, ...
468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480,
481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493,
494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506,
507, 508, 509, 510, 511]), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64)],
'created_at': 0, 'pkg_num': 0, 'event_num': 0, 'name': None}{'window_labels': [[], [], [32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43,
44, 45, 46, 47], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [],
[], [], [], [], [], [], [], [], [], [], [], [], [], []],
'evt_window_labels': [[], [], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [],
[], [], [], [], [], [], [], [], [], [], []], 'data': [array([],
dtype=float64), array([], dtype=float64), array([2053, 2108, 2102, 2078,
2073, 2092, 2099, 2090, 2058, 2074, 2076,
2095, 2094, 2078, 2028, 2069, 2106, 2088, 2072, 2025, 2009, 2082,
2078, 2067, 2068, 2058, 2028, 2054, 2024, 2075, 2074, 2080, 2056,
2046, 2071, 2076, 2054, 2044, 2078, 2085, 2002, 2032, 2040, 2035,
2033, 2046, 2050, 2025, 2033, 2078, 2071, 2040, 2005, 2026, 2044,
2040, 2003, 2040, 2046, 2032, 2055, 2076, 2054, 2025, 2040, 2069,
2082, 2088, 2048, 2046, 2052, 1984, 1664, 1573, 1573, 1620, 1572,
1558, 1529, 1518, 1534, 1541, 1538, 1480, 1491, 1516, 1520, 1477,
1529, 1519, 1459, 1488, 1486, 1500, 1517, 1516, 1590, 1516, 1566,
1554, 1518, 1517, 1528, 1516, 1455, 1446, 1486, 1466, 1488, 1468,
1467, 1452, 1486, 1467, 1510, 1526, 1463, 1492, 1487, 1451, 1491,
1506, 1468, 1491, 1496, 1516, 1493, 1481, 1487, 1493, 1492, 1490,
1470, 1469, 1484, 1502, 1495, ...
1627, 1623, 1618, 1645, 1595, 1614, 1622, 1667, 1606, 1620, 1648,
1619, 1669, 1614, 1640, 1655, 1616, 1638, 1602, 1642, 1625, 1618,
1667, 1621, 1618, 1646, 1624, 1646], dtype=uint16), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64)], 'timing': [[], [], [10488814, 10488814, 10488814,
10488814, 10488814, 10488814, 10488814, 10488814, 10488814, 10488814,
10488814, 10488814, 10488814, 10488814, 10488814, 10488814], [], [], [], [],
[], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [],
[], [], [], [], [], []], 'time': [array([], dtype=float64), array([],
dtype=float64), array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,
26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38,
39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,
52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64,
65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77,
78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103,
104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116,
117, 118, 119, 120, ...
468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480,
481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493,
494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506,
507, 508, 509, 510, 511]), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64),
array([], dtype=float64), array([], dtype=float64), array([],
dtype=float64), array([], dtype=float64), array([], dtype=float64)],
'created_at': 0, 'pkg_num': 0, 'event_num': 0, 'name': None}04/02/2025 10:06
It looks like python can handle about 7.5 MB/s per thread. The performance is slightly better for smaller "chunks" thrown into the algorithm. I.e. if I give the algorithm a times more data it will take a^{1.07} times longer to handle it (i.e the data rate will slow down).
04/02/2025 10:43
Here is the non log version of the plot, just to help
04/02/2025 11:44
Steps I follow to build the simulation:
- Clone https://github.com/PIONEER-Experiment/main
git clone git@github.com:PIONEER-Experiment/main.git
git clone git@github.com:PIONEER-Experiment/main.git - Follow the steps in the README.md for building in a docker container, you can find them on the main page.
- You may need the additional argument to link your ssh id for cloning private repos inside the docker. Check your
~/.sshfor your public key, for example:-v ~/.ssh/id_ed25519:/root/.ssh/id_ed25519
-v ~/.ssh/id_ed25519:/root/.ssh/id_ed25519 - In the docker container edit
/simulation/checkout-branches.shto point to the branches you want, then run:git pull --recurse-submodules ./checkout-branches.sh
git pull --recurse-submodules ./checkout-branches.sh - Then you should be able to build everything with
./setup.sh -aelr. Look at./setup.sh --helpfor information on what each flag does
06/02/2025 12:50
Pi -> e + nu pattern recognition performance:
Pi -> mu + nu pattern recognition performance:
07/02/2025 09:58
"Properly" configured Gaudi option files.
all_dir.opts
//##############################################################
// Job options file
//==============================================================
AuditorSvc.Auditors = { "ChronoAuditor" };
//--------------------------------------------------------------
//--------------------------------------------------------------
// Private Application Configuration options
//--------------------------------------------------------------
ApplicationMgr.TopAlg = { "PIAMainDetRes" };
// Set output level threshold (2=DEBUG, 3=INFO, 4=WARNING, 5=ERROR, 6=FATAL )
MessageSvc.OutputLevel = 3;
//--------------------------------------------------------------
// Event related parameters
//--------------------------------------------------------------
ApplicationMgr.EvtMax = -1;
ApplicationMgr.EvtSel = "NONE";
//--------------------------------------------------------------
// Other Service Options
//--------------------------------------------------------------
PIAMainDetRes.ExecuteFastResponse = 1;
PIAMainDetRes.ExecuteCaloDigitiser = 0;
PIAMainDetRes.OutputFile = "all_dir.root";
PIAMainDetRes.OutputMode = 8064;
SimReader.Files = {"/simulation/test/pimunu_run00000*.root 1"};
FastResponse.RequireTracker = False;
FastResponse.RequireCalo = False;
//##############################################################
// Job options file
//==============================================================
AuditorSvc.Auditors = { "ChronoAuditor" };
//--------------------------------------------------------------
//--------------------------------------------------------------
// Private Application Configuration options
//--------------------------------------------------------------
ApplicationMgr.TopAlg = { "PIAMainDetRes" };
// Set output level threshold (2=DEBUG, 3=INFO, 4=WARNING, 5=ERROR, 6=FATAL )
MessageSvc.OutputLevel = 3;
//--------------------------------------------------------------
// Event related parameters
//--------------------------------------------------------------
ApplicationMgr.EvtMax = -1;
ApplicationMgr.EvtSel = "NONE";
//--------------------------------------------------------------
// Other Service Options
//--------------------------------------------------------------
PIAMainDetRes.ExecuteFastResponse = 1;
PIAMainDetRes.ExecuteCaloDigitiser = 0;
PIAMainDetRes.OutputFile = "all_dir.root";
PIAMainDetRes.OutputMode = 8064;
SimReader.Files = {"/simulation/test/pimunu_run00000*.root 1"};
FastResponse.RequireTracker = False;
FastResponse.RequireCalo = False;
all_rec.opts: (Without Sean's pattern finding)
//##############################################################
// Job options file
//==============================================================
AuditorSvc.Auditors = { "ChronoAuditor" };
//--------------------------------------------------------------
//--------------------------------------------------------------
// Private Application Configuration options
//--------------------------------------------------------------
ApplicationMgr.TopAlg = { "PIAMainRec" };
// Set output level threshold (2=DEBUG, 3=INFO, 4=WARNING, 5=ERROR, 6=FATAL )
MessageSvc.OutputLevel = 3;
//--------------------------------------------------------------
// Event related parameters
//--------------------------------------------------------------
ApplicationMgr.EvtMax = -1;
ApplicationMgr.EvtSel = "NONE";
//--------------------------------------------------------------
// Other Service Options
//--------------------------------------------------------------
PIAMainRec.InputFile = "all_dir*.root";
PIAMainRec.InputTree = "rec";
PIAMainRec.InputMode = 8064;
PIAMainRec.OutputFile = "all_rec.root";
PIAMainRec.OutputMode = 1515392;
//PIAMainRec.OutputMode = 0;
PIAMainRec.ExecuteTruthTrackletFinder = 1;
PIAMainRec.ExecuteTruthPatternFinder = 1;
PIAMainRec.ExecutePionStopLocator = 1;
PIAMainRec.ExecuteMudifDiscriminant = 1;
PIAMainRec.ExecutePatternFinder = 0;
PIAMainRec.ExecuteCaloSingleHitFinder = 0;
PIAMainRec.ExecuteCaloClusterFinder = 1;
PIAMainRec.ExecuteSummaryCollector = 1;
PIAMainRec.ExecuteHistogrammer = 1;
CaloClusterFinder.SpaceThr = 60;
Histogrammer.filename = "all_hst.root";
Histogrammer.calib = "lyso_cal.txt";
Histogrammer.cuts = {
"time TimeWindow all;-300 -5;5 500",
"box AtarBox time 8 8 1.2 4.8",
"fid FidTheta box 120",
"1p SinglePattern fid",
"3c TrippleDep 1p 2",
"edep PromptLateEdep 1p 10.8 4.5",
"kink AtarKink edep",
"doca Doca kink 0.2 0.12",
"init InitStopDEDX doca 6.4",
"dedz DelayedDEDZ init 1.5",
"tkr1 HasTracker fid",
"tkr2 HasTracker dedz"
};//##############################################################
// Job options file
//==============================================================
AuditorSvc.Auditors = { "ChronoAuditor" };
//--------------------------------------------------------------
//--------------------------------------------------------------
// Private Application Configuration options
//--------------------------------------------------------------
ApplicationMgr.TopAlg = { "PIAMainRec" };
// Set output level threshold (2=DEBUG, 3=INFO, 4=WARNING, 5=ERROR, 6=FATAL )
MessageSvc.OutputLevel = 3;
//--------------------------------------------------------------
// Event related parameters
//--------------------------------------------------------------
ApplicationMgr.EvtMax = -1;
ApplicationMgr.EvtSel = "NONE";
//--------------------------------------------------------------
// Other Service Options
//--------------------------------------------------------------
PIAMainRec.InputFile = "all_dir*.root";
PIAMainRec.InputTree = "rec";
PIAMainRec.InputMode = 8064;
PIAMainRec.OutputFile = "all_rec.root";
PIAMainRec.OutputMode = 1515392;
//PIAMainRec.OutputMode = 0;
PIAMainRec.ExecuteTruthTrackletFinder = 1;
PIAMainRec.ExecuteTruthPatternFinder = 1;
PIAMainRec.ExecutePionStopLocator = 1;
PIAMainRec.ExecuteMudifDiscriminant = 1;
PIAMainRec.ExecutePatternFinder = 0;
PIAMainRec.ExecuteCaloSingleHitFinder = 0;
PIAMainRec.ExecuteCaloClusterFinder = 1;
PIAMainRec.ExecuteSummaryCollector = 1;
PIAMainRec.ExecuteHistogrammer = 1;
CaloClusterFinder.SpaceThr = 60;
Histogrammer.filename = "all_hst.root";
Histogrammer.calib = "lyso_cal.txt";
Histogrammer.cuts = {
"time TimeWindow all;-300 -5;5 500",
"box AtarBox time 8 8 1.2 4.8",
"fid FidTheta box 120",
"1p SinglePattern fid",
"3c TrippleDep 1p 2",
"edep PromptLateEdep 1p 10.8 4.5",
"kink AtarKink edep",
"doca Doca kink 0.2 0.12",
"init InitStopDEDX doca 6.4",
"dedz DelayedDEDZ init 1.5",
"tkr1 HasTracker fid",
"tkr2 HasTracker dedz"
};all_rec.opts (with Sean's pattern finding)
//##############################################################
// Job options file
//==============================================================
AuditorSvc.Auditors = { "ChronoAuditor" };
//--------------------------------------------------------------
//--------------------------------------------------------------
// Private Application Configuration options
//--------------------------------------------------------------
ApplicationMgr.TopAlg = { "PIAMainRec" };
// Set output level threshold (2=DEBUG, 3=INFO, 4=WARNING, 5=ERROR, 6=FATAL )
MessageSvc.OutputLevel = 3;
//--------------------------------------------------------------
// Event related parameters
//--------------------------------------------------------------
ApplicationMgr.EvtMax = -1;
ApplicationMgr.EvtSel = "NONE";
//--------------------------------------------------------------
// Other Service Options
//--------------------------------------------------------------
PIAMainRec.InputFile = "all_dir*.root";
PIAMainRec.InputTree = "rec";
PIAMainRec.InputMode = 8064;
PIAMainRec.OutputFile = "all_rec.root";
PIAMainRec.OutputMode = 1515392;
//PIAMainRec.OutputMode = 0;
PIAMainRec.ExecuteTruthTrackletFinder = 1;
PIAMainRec.ExecuteTruthPatternFinder = 0;
PIAMainRec.ExecutePatternFinder = 1;
PatternFinder.UseTrackletTimeOrder = true;
PatternFinder.DeltaRThreshold = 1.0;
PIAMainRec.ExecutePionStopLocator = 1;
PIAMainRec.ExecuteMudifDiscriminant = 1;
PIAMainRec.ExecuteCaloSingleHitFinder = 0;
PIAMainRec.ExecuteCaloClusterFinder = 1;
PIAMainRec.ExecuteSummaryCollector = 1;
PIAMainRec.ExecuteHistogrammer = 1;
CaloClusterFinder.SpaceThr = 60;
Histogrammer.filename = "all_hst.root";
Histogrammer.calib = "lyso_cal.txt";
Histogrammer.cuts = {
"time TimeWindow all;-300 -5;5 500",
"box AtarBox time 8 8 1.2 4.8",
"fid FidTheta box 120",
"1p SinglePattern fid",
"3c TrippleDep 1p 2",
"edep PromptLateEdep 1p 10.8 4.5",
"kink AtarKink edep",
"doca Doca kink 0.2 0.12",
"init InitStopDEDX doca 6.4",
"dedz DelayedDEDZ init 1.5",
"tkr1 HasTracker fid",
"tkr2 HasTracker dedz"
};//##############################################################
// Job options file
//==============================================================
AuditorSvc.Auditors = { "ChronoAuditor" };
//--------------------------------------------------------------
//--------------------------------------------------------------
// Private Application Configuration options
//--------------------------------------------------------------
ApplicationMgr.TopAlg = { "PIAMainRec" };
// Set output level threshold (2=DEBUG, 3=INFO, 4=WARNING, 5=ERROR, 6=FATAL )
MessageSvc.OutputLevel = 3;
//--------------------------------------------------------------
// Event related parameters
//--------------------------------------------------------------
ApplicationMgr.EvtMax = -1;
ApplicationMgr.EvtSel = "NONE";
//--------------------------------------------------------------
// Other Service Options
//--------------------------------------------------------------
PIAMainRec.InputFile = "all_dir*.root";
PIAMainRec.InputTree = "rec";
PIAMainRec.InputMode = 8064;
PIAMainRec.OutputFile = "all_rec.root";
PIAMainRec.OutputMode = 1515392;
//PIAMainRec.OutputMode = 0;
PIAMainRec.ExecuteTruthTrackletFinder = 1;
PIAMainRec.ExecuteTruthPatternFinder = 0;
PIAMainRec.ExecutePatternFinder = 1;
PatternFinder.UseTrackletTimeOrder = true;
PatternFinder.DeltaRThreshold = 1.0;
PIAMainRec.ExecutePionStopLocator = 1;
PIAMainRec.ExecuteMudifDiscriminant = 1;
PIAMainRec.ExecuteCaloSingleHitFinder = 0;
PIAMainRec.ExecuteCaloClusterFinder = 1;
PIAMainRec.ExecuteSummaryCollector = 1;
PIAMainRec.ExecuteHistogrammer = 1;
CaloClusterFinder.SpaceThr = 60;
Histogrammer.filename = "all_hst.root";
Histogrammer.calib = "lyso_cal.txt";
Histogrammer.cuts = {
"time TimeWindow all;-300 -5;5 500",
"box AtarBox time 8 8 1.2 4.8",
"fid FidTheta box 120",
"1p SinglePattern fid",
"3c TrippleDep 1p 2",
"edep PromptLateEdep 1p 10.8 4.5",
"kink AtarKink edep",
"doca Doca kink 0.2 0.12",
"init InitStopDEDX doca 6.4",
"dedz DelayedDEDZ init 1.5",
"tkr1 HasTracker fid",
"tkr2 HasTracker dedz"
};