mpw-002 / URPM Ultra-high resistor poly mask

the URPM shapes of all of mpw-002

40 of 40 dies rendered.

126 shapes in total, each die at 0.125 µm per pixel.

result.json · job.json · reticle overview PNG

1234567
A A1 A2 A3 A4 A5 A6
B B1 B2 B3 B4 B5 B6 B7
C C1 C2 C3 C4 C6 C7
D D1 D2 D3 D4 D5 D6 D7
E E1 E2 E3 E4 E5 E6 E7
F F1 F2 F3 F4 F5 F6 F7

Downloading the full-resolution image

The stitched reticle is 53,432×65,056 pixels — 3.48 gigapixels. The file itself is small, but decoding it needs about 3.5 GB of memory however small the file is, and most viewers refuse it outright. So it is also published as 42 tiles of about 7576×10776 px (4.4 MB in total, largest 110.9 kB), cut in the gaps between dies so that every tile holds whole projects and none is split.

To put the full-resolution PNG back together from them, byte for byte, with nothing installed but Python itself:

python3 reconstruct_reticle.py

Run it in a directory holding the tiles and mpw-002_URPM_tiles.json and it finds them itself, checks every tile against its checksum as it reads it, and checks the finished file against the manifest. It works because the tiles and the full image are written with PNG's Up filter, which never looks at the pixel to its left — so a row of tiles' scanlines laid end to end is the full image's scanline, and rebuilding moves bytes rather than doing pixel arithmetic.

Whole-reticle files

FileSizeMD5SHA-1SHA-256
mpw-002_URPM_reticle.png
the stitched reticle, full resolution
3.5 MB 1b7aac2c6313ec145d0a7c9cc00680ab3af5e9c973a5a4a4db9dd158de67c78eba8748c5 a269cb70a6233ef9b4dfd87b8faff8fb9a399924ff77efae05def9c624b545ec
mpw-002_URPM_reticle_overview.png
the same image scaled to fit 4096 px
14.6 kB b4d49a67a7552fbecdb670510f6722d26394443a1ba4ed9758cbc85307811a33c43f5560 85dafe549a6ae4de838c0b629558f6618d00981ec301824dfe9c3dfbb18cbe68
mpw-002_URPM_tiles.json
where every tile belongs, and its checksum
13.3 kB c2e568376ac8ff9cc5a4c3a15ddb3cde6cf1d2dff93e416f1c0538bc6567b8f1d4fbc7db 6213345e740a527835b3e64d5351c6fffa839fd01c126d1d5e91916823d572f3
reconstruct_reticle.py
rebuilds the reticle from the tiles, standard library only
11.9 kB 4406f1f3db8a4a85756610b7c432c47a294714566ceb084187594ced0020f9260faac32a d2e72bf4b2541f1a8acb11eb758917c5b5fa080b41b3a7118487c03f8af2a769

Every file in this directory is listed in MD5SUMS · SHA1SUMS · SHA256SUMS, in the format the standard tools read:

sha256sum -c SHA256SUMS

The 42 tiles

FrameProjectPixelsPositionSizeSHA-256
A1 axi_dma_using_spinal 7576×107760, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A2 wishbone_can 7576×107767576, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A3 Analog-Neural-Network 7576×1077615152, 0 103.1 kB925d97eb7c2c3c41e2e56e8c4203eab3825e989534172b2b031839ed1cf17292
A4 caravel_dsp2 7576×1077622728, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A5 eFPGA_v3_caravel 7576×1077630304, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A6 opencryo_testchip 7576×1077637880, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 yiFive 7576×107760, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B2 lexicon 7576×107767576, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B3 ucsc_openram_test_chip_v2 7576×1077615152, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B4 yonga-lz4_decoder 7576×1077622728, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B5 Potentiometric_Digit 7576×1077630304, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B6 fuserisc_ver2 7576×1077637880, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B7 amsat_txrx_ic_mpw2 7976×1077645456, 10776 107.7 kBc66cf0a59eed5d3ee90cc6d4fe413e78e435331b8bd5aa6e10c146a8bdc4d3ae
C1 Comparator_3v3 7576×107760, 21552 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
C2 caravel_multi_encode 7576×107767576, 21552 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
C3 kasirgalabs_uart 7576×1077615152, 21552 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
C4 Automatically_genera 7576×1077622728, 21552 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 uqab 7576×1077637880, 21552 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
C7 caravel_azadi_soc 7976×1077645456, 21552 106.9 kB24fc4f09b4bd28cada855bff8a84875c9d42464781d49f18223fedf9c060cb09
D1 caravel_dsc 7576×107760, 32328 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
D2 SOFA-Plus-eFPGA 7576×107767576, 32328 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
D3 caravel_user_project 7576×1077615152, 32328 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
D4 General_Purpose_Band 7576×1077622728, 32328 103.1 kBcc214a1bf44df8fdc88d882aa472b284238e433c93d4cf41529bf8200feb16ec
D5 zero_to_asic 7576×1077630304, 32328 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
D6 fast_gcd_for_large_i 7576×1077637880, 32328 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
D7 Columbus 7976×1077645456, 32328 106.9 kB24fc4f09b4bd28cada855bff8a84875c9d42464781d49f18223fedf9c060cb09
E1 Space_shuttle 7576×107760, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E2 subservient 7576×107767576, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E3 caravel_analog_fulgor 7576×1077615152, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E4 bandgap_reference_de 7576×1077622728, 43104 103.1 kB13939880d7e2f06583bc77e130aae4b3c8893db79041ed5daa396eed1ec224e7
E5 renml 7576×1077630304, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E6 io_expander 7576×1077637880, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E7 digital_pll 7976×1077645456, 43104 107.4 kB6fb6f09f61dddcf11de83d81b8950db7b15c73dd86597a4a390ce67634b3080f
F1 zero_to_asic 7576×111760, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F2 caravel_fpu 7576×111767576, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F3 BrqRV_EB1 7576×1117615152, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F4 hilas 7576×1117622728, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F5 vlsi-sky130-analog-c 7576×1117630304, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F6 sha1_engine 7576×1117637880, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F7 caravan_openfasoc 7976×1117645456, 53880 110.9 kBf4003129e59f6711282296e4e6ff16c7a66ed7d6da5e53cd32fc7a676a5b7686

Position is the tile's top-left corner in the full-resolution image. MD5 and SHA-1 for the same files are in the checksum files linked above.

About URPM on mpw-002

Resolved: reticle 5CS8007AC, run mpw-002, mask URPM

Mask layer
URPM — Ultra-high resistor poly mask
Process step
55 — Ultra-high resistor poly mask
Drawn layer
79:20

mpw-002 — SKY130 MPW-2

Foundry product
EF MPW#2
Reticle set
5CS8007AC
Run date
2021-06-18
Submissions closed
2021-06-18
Projects
56
Fab lot
4205819
Identification
confirmed — Lot records: EF MPW#2, lot 4205819 = 'SKY130 MPW 2'
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-2 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-002/foundry

These are renders of the drawn shapes that go on each photomask, taken from the layouts the shuttle's projects taped out — they are not photomask artwork: reticle pitch, the 4x reduction, mirroring and the frame features the fab adds are not modelled. An empty image is a real result; several mask layers are used by no project on a given shuttle. Each die's source layout is named in result.json and lives in the public shuttle repositories under foss-eda-tools.googlesource.com, so every image here can be traced back to the tape-out it came from. Generated with sky130-mask-decoder.