mpw-003 / VIPDM Pad Via

the VIPDM shapes of all of mpw-003

40 of 40 dies rendered.

34,042,818 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 (13.8 MB in total, largest 473.1 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-003_VIPDM_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_VIPDM_reticle.png
the stitched reticle, full resolution
9.5 MB a4f47b43081da04e37cc64b891ad727d9e6dfd9ccbd7058ffc2b671dff0b6e16e17ec16f cff4dd13c97de8034bbb740bc3f6469eb9e78b1d81e839760064a7b500c5ada7
mpw-003_VIPDM_reticle_overview.png
the same image scaled to fit 4096 px
406.7 kB bbab392914e71a175e880ba7fb8706460b2fc618c9e53ba159414024c913701e08e537cc c372f584b09c654572b48c11557ddd2a5d3c29c9471b52b8485ce4b0c23fb547
mpw-003_VIPDM_tiles.json
where every tile belongs, and its checksum
13.5 kB ae59d371dc42f200b2cda01365c09d95ef872f2e00b778c6e1ed1aac75a10fe19fc2ed00 641dc5bd5ec6cb960330ab3c695429bfd6c4005b047a8d8479a9fe06042fe76b
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, 0 321.1 kB9f1765ba3b12efb8fed82dc8a5beb2839ed9cb41af12a9fd4f55e33272886aa2
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 304.5 kBf87d6147e1b62433952acc2af95b2b478eb90e51149b0069daeba39193bf5b29
A3 openram_test 7576×1077615152, 0 326.1 kBd7f6f6737876aab47efe28654fba5f4c2d12c9f61c61045b898f386abd7e1163
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 353.4 kBc7e9742a78eabe1b3ba26a6243ff693c001fa418d73d382c0655a02428bdb32a
A5 crypto_accelerator_v2 7576×1077630304, 0 345.8 kB6dd00bbf4c9b1e6ce1ccb6aae8d914cfb0c2f2bdc8e0ad52a75bc412bae878ec
A6 picorf0 7576×1077637880, 0 335.9 kBcc519867ac50f73e23fd8a872270e8926bc618fe95cfb6bdea6c02748fd6467d
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 322.8 kBaf72927dae6e115eb6d5ca6473f91f3593d117b230d0ae29cf830500330fca55
B2 yonga-100m_ethernet 7576×107767576, 10776 331.5 kB488b48c11cf96cc51c725923793aeeb322c998d6ceb17e9f4314d584d9b3e180
B3 approximate_multiplier 7576×1077615152, 10776 321.4 kB9006a949880d89598e958b38fa53e9571b691b6b4d2fae7cee003bc1ecc07c15
B4 vsd 7576×1077622728, 10776 314.9 kB5abc493abd36f1b195c5d2a8b4f9408bb3ac3e6b216f9cc55e7ec478baa68aaa
B5 asic_key_value_store 7576×1077630304, 10776 321.1 kB9f1765ba3b12efb8fed82dc8a5beb2839ed9cb41af12a9fd4f55e33272886aa2
B6 mbist_controller 7576×1077637880, 10776 426.0 kBccc93f0bfe7309794315886fe8cfa0ceeed9e6662181727b339fa9a892cc698e
B7 riscduino 7976×1077645456, 10776 425.6 kB63d49f92ae8db7f647b53f3a2f029f97c7adab9c23f5a6ec79e70a74ac57d602
C1 caravel_peripheral_extender 7576×107760, 21552 333.4 kBb43cf3bc907b3c6ac97401e7d849f3739656f435376a5e74154d465fdb2808f8
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 473.1 kB4b6f526a901bb2476c9cb099dc48ee2820b3e0f908a21671e2bfd1d8ad56befe
C3 class-d_audio_amplifier 7576×1077615152, 21552 337.1 kB8e8767bd2ed28c393d5c1f2bbe52b94493e77f4d63596e2118c79c4f101b8269
C4 efabless_processor 7576×1077622728, 21552 321.1 kB9f1765ba3b12efb8fed82dc8a5beb2839ed9cb41af12a9fd4f55e33272886aa2
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 316.0 kB52471845b678f6fc03ea1cfcc371c02820e46f0e803b8e469174d9a0d8cd7389
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 298.7 kBdc6f4ecb5593237dfa57347291b27f105925da4ccd9c86736d50e6ffbba8bdca
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 291.7 kB290187dad6614d5529b75782085fe3f5e97783908cdbed56da8a1030699d4b70
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 291.7 kB290187dad6614d5529b75782085fe3f5e97783908cdbed56da8a1030699d4b70
D3 sziklai_pair_amplifier 7576×1077615152, 32328 291.7 kB290187dad6614d5529b75782085fe3f5e97783908cdbed56da8a1030699d4b70
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 291.7 kBe0b9eda026f7af6ab095c768ae5d10bc0378f52eb83bd3a1490bc8abf9c0a25d
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 343.6 kB0dfbd1fba4e59bed6223a628575dac8680ca95d60e1ef2d25a044bf185b569c1
D6 rotfpga 7576×1077637880, 32328 326.5 kBccfd219a35578d759d82cac6dffa68a78d76ea6d023bd02276e4a7553ee3ce4e
D7 treepram 7976×1077645456, 32328 434.2 kB7fc1f5fc5a3082ece77f232ec5c868cef5e6b7b9e01ae4793dd9f1bb6c9fdf95
E1 treepram-red 7576×107760, 43104 472.6 kB2a5747806a998b831742aa25b08d928159f533a77129e69ed204178cd21f7432
E2 caravel_jacaranda-8 7576×107767576, 43104 331.1 kB4c1608dde5d63637a0291c84e501e89e40e39b09f5cbbfeeacd328c941129022
E3 sudoku_accelerator 7576×1077615152, 43104 334.3 kBad1553d7fa191a0ef0610bffc6450b7b672a806b50b45b43b6c4e6a59f0c29f7
E4 fixed2float_converter 7576×1077622728, 43104 321.2 kB18c14f008c263cdd6cf8d1aa1b91bf42b58c3b29d661d6719dbc2bc7a3df563b
E5 high_speed_adder 7576×1077630304, 43104 312.3 kBbc14def72bc6f64fc0f0f742768393b7ecd4bc0d65a7431f400614fbcce9f666
E6 my_proj 7576×1077637880, 43104 321.2 kBf1c250753b96035a404d063d983cc54de5bcfde292ae2203a719968a7c767e68
E7 pwm_test 7976×1077645456, 43104 328.0 kB92452bc86cf3a9add3d2557773941127f17f827ad6cdf15639117ce6578faf1d
F1 elpis-light-mpw3 7576×111760, 53880 431.3 kB19ef69c493a2451b899556557b8ab4dc42c05647483b0d60598e5c657df2ba99
F2 vsdbabysoc 7576×111767576, 53880 340.2 kBd8dd64aa9a7173feaf083088a869742bfc26a44e6ec4a9f87cd52ad796a9b8a0
F3 vsdmemsoc 7576×1117615152, 53880 360.2 kB02d8ed61ee7f5d34e52556ecae8b9e57d40465b74d195cf5c319757ea4f317d1
F4 caravel_sram_test 7576×1117622728, 53880 324.8 kBab7280eaf10e9d42fcbdd2e7d0c870292dcbfa4d490233ec36287a7ba5d07b2f
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 299.7 kB1042223c90ca5eaf25657ece7e1836834be0c0a4b333f89173701a23de321590
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 330.1 kB5463e072a27df5686e6ea011b0d17eb4679b787671c5b237eb3303141d3ecb0e
F7 caravel 7976×1117645456, 53880 332.3 kBcba08a5efbd1e606553c4bb1b47f7af676c908e79a6473bb349c251ae8899aee

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 VIPDM on mpw-003

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

Mask layer
VIPDM — Pad Via
Drawn layer
70:44
Detail
VIPDM = via3 (pad-via flow, not SKY130)
Used in SKY130
no

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.