mpw-003 / NWM N-Well*

the NWM shapes of all of mpw-003

40 of 40 dies rendered.

22,069,449 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 (20.1 MB in total, largest 1.1 MB), 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-003_NWM_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-003_NWM_reticle.png
the stitched reticle, full resolution
12.8 MB 8d732a393d8f8cc758c14d65604e87d8c03eb5c22cf6d9b902ba4038bc94e89447bb841f 076bef12655968d729d1802e3cb902d9e0a3dbe603ed4432415e3bf1a5437ad0
mpw-003_NWM_reticle_overview.png
the same image scaled to fit 4096 px
1.3 MB c961b9b510ffae68ed15b2a2d3e338139e105938d140b6f404fcf48294fa7c83275ce0b1 964ae71469bea12ecc0dc5ec881e8d1f6ccf90621d902123bc6cb7bee1de8d69
mpw-003_NWM_tiles.json
where every tile belongs, and its checksum
13.4 kB 95c77846383b3c6ea16d25b5ccc63c0831da0a2702d021d0b560470e0b9a6a025be6be44 784e8c0fb7bb0998829dfdd82fb6b6d67e4da8864b8605af5ad3ff637e237c27
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 stdcelllib 7576×107760, 0 417.8 kB4103f3599dc08544f8450d9188870c183b83222af1e355d3b997288351084ad8
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 396.2 kB08852ab137bfe1d606b9454e25316df39594a18c7dc0d3456782c2b11b99441a
A3 openram_test 7576×1077615152, 0 415.5 kB4ebee6aa94eee466b5e4b7835abd3e7da657c149237ccb0fa011dd78bd3bee9c
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 510.6 kBa4697460448a1ad19384a1c5fd0d9495acc1e8d1213f5378b2b579d1371887af
A5 crypto_accelerator_v2 7576×1077630304, 0 660.8 kB57dd66680b588fd0f9f2b90d2db0e06fe60a76d506d820450c6a2f9d5d431da4
A6 picorf0 7576×1077637880, 0 497.2 kB331a3d52b63b312c96efcfa3e61df062354e0b089011cde38bb317d32f92cd5c
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 438.0 kB3e784a638e882f4812ea7de1f8c05080bfc518ceb40573bec4d6d8e9c67c3f59
B2 yonga-100m_ethernet 7576×107767576, 10776 489.1 kB2e9ecfd24939bb82fde7b2034ff9485c1f46332be6d344bc2036b10530946229
B3 approximate_multiplier 7576×1077615152, 10776 403.2 kBfe76692d973c3a298accc08881c63fa22cb53c0b6cd6b3915b4485c4ffdecf20
B4 vsd 7576×1077622728, 10776 408.7 kBa7006fa1f987fdba5c9f660236cd68b20140a3093a4648759b34516d56f0f478
B5 asic_key_value_store 7576×1077630304, 10776 417.8 kB4103f3599dc08544f8450d9188870c183b83222af1e355d3b997288351084ad8
B6 mbist_controller 7576×1077637880, 10776 554.9 kB2af9797fd391066240a4a70fabfe5d75aa29757408d1284a96b02dc68c71305a
B7 riscduino 7976×1077645456, 10776 685.3 kB2fc15d8e14190ec9dbd4e8c7f3db77cdfc88d6ed398c7d655142d902e906cbb7
C1 caravel_peripheral_extender 7576×107760, 21552 456.2 kB7bde745cfb163884fc40cadcf0aec88cd3e0a4cd9174fb16c11bcdc2a18e7621
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 572.7 kB1b3bdbd0a13b3398035831879d9083384f880872a9590ffaf937679b95e575b1
C3 class-d_audio_amplifier 7576×1077615152, 21552 394.2 kB7410493fe1163911653b13bde08f368f0c33c8c7682cdca774ddfda5c1ec52c5
C4 efabless_processor 7576×1077622728, 21552 424.4 kB7c682c4c69abcacfa75fdc8e02e28cfe654cc22c3aee29d3aece49ca9db837dc
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 402.1 kBbad9cc678d29cba7908c75dc1ff880e3d467f50df858ea55591dd092800a7c73
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 396.9 kBace393bf48f71d8ef704e2adb95061ed198ac150cd850083a32eb9f5fba5c147
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 395.4 kB0abfcaa4a043b9e32a59558348ca2626e653ab27ac885ea32d501f4b950f7851
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 408.5 kB2a2bf0a89e30fe6b2115c334ab9bddf618f4951e0b385d40d67eb4bab20a3cd5
D3 sziklai_pair_amplifier 7576×1077615152, 32328 395.4 kB12044d434b395f7e75df3351407e3e98ea1ef37721723005c4648f87aa9b71d6
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 395.5 kBd80857a686a7840900eb768fb293f015c4a06b7e2b4e747cf87c780c6518c2c4
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 499.5 kBbad9fd7028b01aed402cd10a347367c2a0da5fa1e0134fb7ae2dfcd0dd2dbcc1
D6 rotfpga 7576×1077637880, 32328 450.7 kB8ad38fa62dde0caceb074da6f2c2dd53200efea198fd60a1fe33f52bc0397972
D7 treepram 7976×1077645456, 32328 968.0 kBaf0a300ae8ca64dbebd56a50947185a4fbb2d26dac68fb5d99acd7e5ab3816c0
E1 treepram-red 7576×107760, 43104 990.6 kBb12ac5f244e5931417f6872f0c6c64c83f47fd4dd915e723ec34ffacb140129b
E2 caravel_jacaranda-8 7576×107767576, 43104 467.3 kB536d12034502e3796ea888078a8633ba63403d80b78575edead224d9215cfb8b
E3 sudoku_accelerator 7576×1077615152, 43104 505.1 kBe4f361257dac2a7833920ee5b979f8dbca499e47c11ab08ea46121d131690864
E4 fixed2float_converter 7576×1077622728, 43104 417.5 kB4540fc60a99e828172873fc1d9c70fd734c20aaa91370b67dd9ee84b56dc1475
E5 high_speed_adder 7576×1077630304, 43104 405.8 kB9eb4dcb1f4616b8760ec7892fc9c4400a8bb0af53c4e340aa04f3dd70783de71
E6 my_proj 7576×1077637880, 43104 415.6 kB2c01ac3aac1699ec670a4c4214aad98b54643909cb9ddbfd905213795e596b93
E7 pwm_test 7976×1077645456, 43104 422.2 kBcd00725a1ca1f81f01cd546263d10e6e962a82d4d4f33ef6482aa84dd63e3d78
F1 elpis-light-mpw3 7576×111760, 53880 1.1 MB73beec12c6f57462ae50ab3108e5a2ca538494f794ab0a48aa806d2fabaa7f81
F2 vsdbabysoc 7576×111767576, 53880 527.6 kBe80166f1e4b5e454a39c36daf101c74d6cfec664daa6289503fb5b3cc11b8b90
F3 vsdmemsoc 7576×1117615152, 53880 562.3 kB8823847b877b36ca2d50682e70d4c3a269b69c7d379f3f68aec10e065962d784
F4 caravel_sram_test 7576×1117622728, 53880 415.1 kB590861c90db8f61df5c5d5a149d9c83b467859ac4b7d62472f8262d6961e1fc3
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 398.5 kB6853ca3660fd0e1fd886bb4ed4d2d7f8e3bf671ac9c42b73ec9807fe510df2e7
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 419.5 kB073c2f0e079001ce453e5db90ca49c8ee80d597432bd1b209833ba5eab336a85
F7 caravel 7976×1117645456, 53880 421.6 kB90fcdba790aa34bd62ba0381f46031ee873fe64cc7ae380a2a6c2fe525bd8595

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 NWM on mpw-003

Resolved: reticle 5CS8008AC, run mpw-003, mask NWM

Mask layer
NWM — N-Well*
Process step
17 — N-well mask
Drawn layer
64:20
Layer on the mask-layer GDS
21:0
Detail
NWM = nwell sized (cnwm.3a outside hvi / 3b inside), with DEPMOS/pwell-resistor exemptions
Used in SKY130
yes

mpw-003 — SKY130 MPW-3

Foundry product
EF MPW#3
Reticle set
5CS8008AC
Run date
2021-11-15
Submissions closed
2021-11-15
Projects
53
Fab lot
4206521
Identification
confirmed — Lot records: EF MPW#3, lot 4206521 = 'SKY130 MPW 3'; confirmed by a photo of the MPW-3 mask set's VIM2 plate label (DEVICE 5CS8008A-A, LAYER VIM2 560A 03-01, archived 2022-05-13), seen 2026-08-28
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-3 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-003/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.