mpw-003 / VIM Via

the VIM shapes of all of mpw-003

40 of 40 dies rendered.

65,385,010 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 (66.1 MB in total, largest 3.7 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_VIM_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_VIM_reticle.png
the stitched reticle, full resolution
34.5 MB 4f6b1b1d7958dc2ba9f1f08f7456221fdc77ee5398a1012b2d1bdb4b8602dc1f571df388 86297566c7f47a64b84af2dfd4b34023cbc3c9cffc14883ea8743207858452eb
mpw-003_VIM_reticle_overview.png
the same image scaled to fit 4096 px
726.0 kB 3b5d74eb23b150d3eb17c2bbb5d91126855cf08dd5c3a880852c21a80feae3b8fa63a5d2 83be64e2307af7726dc75811daaf731c4cf59408b7d6a23f390cc64d4738d772
mpw-003_VIM_tiles.json
where every tile belongs, and its checksum
13.5 kB 640d1bc7b457038d0690a992cf92e4da8a2d351773c4ccac9ac0b0d65017c348e388716a 27ab9cd6b870c525f32f2ae2d3c51df4a8f7d25e103addaaf5e909ecd9925288
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 1.4 MBf7a7eea129a4d504b38b271f80c0459d0fba9bb5e6a23106d34c1fff0eb0c3c5
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 1.4 MB3c9609f1653438283df388a12747d1231be31f7ee329144e19a57e08527ff689
A3 openram_test 7576×1077615152, 0 1.4 MB190636a25ad8515b50bd0c9bc8c507a762d404d4fbed8b7db0d3ac63287ebbae
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 1.7 MB4b50f44560be18f26a27584f24b6eb114a90bbcaafb63cc6eabcd8f371740cc7
A5 crypto_accelerator_v2 7576×1077630304, 0 2.0 MB6028d33958262f7016e83882be426cad5e595646f0cb66f3a5ef736813f77ebb
A6 picorf0 7576×1077637880, 0 1.6 MB96bd8348bd6ba6b538acb25e690434a0f585699855d889289c02e29b39e6d931
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 1.5 MBaa886d835a7a9bd01ef908836845bc2b0caefb9c07c8c876b5fd838945d75b80
B2 yonga-100m_ethernet 7576×107767576, 10776 1.7 MBe909eac267f5c952cf04392ec4b3571acb38f466a3e93a120724a6ab42aa1df9
B3 approximate_multiplier 7576×1077615152, 10776 1.4 MB85c555053cf3b970d97791654936031aebfbe3c57dd60f52b70aec6cdccf28e2
B4 vsd 7576×1077622728, 10776 1.4 MB49184f57d2dc1442abf795543d7b4a3b83e22443544211601f9f9cc9bd8a31cc
B5 asic_key_value_store 7576×1077630304, 10776 1.4 MBf7a7eea129a4d504b38b271f80c0459d0fba9bb5e6a23106d34c1fff0eb0c3c5
B6 mbist_controller 7576×1077637880, 10776 1.8 MB8ea81a6a7e6f4ff405c58ea3370cf8efc61e2f1c2969693fb8b32b1dcf4428f9
B7 riscduino 7976×1077645456, 10776 2.3 MB253c977bdd9f0adcb92823e9fc39a84891de7b5e4a3305a153dfd2f33894e02d
C1 caravel_peripheral_extender 7576×107760, 21552 1.7 MBa1706c61276995d19dcaf804c2c7712150598c1d0c270c4380b60733a7831e33
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 1.6 MB8a016be474cf426f0e5683729dcd962434d3412c61fdeb8557920af5ae801b37
C3 class-d_audio_amplifier 7576×1077615152, 21552 1.4 MBa3087b2f955b6500c7872058dcd16f20d453e2b43e3eff16713427fae2107697
C4 efabless_processor 7576×1077622728, 21552 1.4 MB64dfc32f2454440686083f6acf609f4775105a3cdc1b3eb662d07c6da21a44a6
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 1.4 MBa8ca5469403200ca5e97fff4e2dc045fd681f5a2833c44a2e2050912cec5b7b7
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 1.3 MBa1eb215c3aec8228f63c2bf04830e9fdc2430202c00893e5a874a3cc79d0bcda
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 1.3 MBe0f1a1d7529a4bb6b104166399f347a211720af0cbbbd78b726019631c0ade7c
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 1.3 MB3937c06a3e5f18df76df399b06ba77956bc79b7e7938a0f669877c1e042bd4f6
D3 sziklai_pair_amplifier 7576×1077615152, 32328 1.3 MB9bc0753dec762d313d5cb1b8e90caaed11c5134d758a60646ff335e370e6fd3b
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 1.3 MB9bc0753dec762d313d5cb1b8e90caaed11c5134d758a60646ff335e370e6fd3b
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 1.9 MB0e47f4dacd2810381071814d31f589f3751a1713dd7d6f2505a4a408ed6c2677
D6 rotfpga 7576×1077637880, 32328 1.6 MB6cbd79728277740be025a4a726c67e459479f1ebd13b407e66556b650268f96e
D7 treepram 7976×1077645456, 32328 3.1 MBf1cd14b2f7b6735ced8a22510b962d860ad9a64bb4b0b797a333f8fda168cc04
E1 treepram-red 7576×107760, 43104 3.7 MB5c7fcce194c79d3dfca94494ac92a8422c4ff0a2e293df1a488bb6cb8ea3bbe0
E2 caravel_jacaranda-8 7576×107767576, 43104 1.6 MBcbdbfa17b4dc402df17b5c9563ccdfc1df237d93a7c5cd874141440417ee9a4f
E3 sudoku_accelerator 7576×1077615152, 43104 1.8 MB091613aa3e0b47950ba619f209994e9584c2edad3629b5329727310431ca2886
E4 fixed2float_converter 7576×1077622728, 43104 1.4 MB4b95fb57e8ec44e31ea5ce11d882186f48329ce0151cee37f065ff36dbe2c761
E5 high_speed_adder 7576×1077630304, 43104 1.4 MBa3b03f21b5973465828d502d73b76726db3dc41d133b1f2e66d80f1e7710ae78
E6 my_proj 7576×1077637880, 43104 1.4 MB6b522cd8a0755192b9e86ecf2e348cee184751d1582cf9882fb0c5425cc68628
E7 pwm_test 7976×1077645456, 43104 1.4 MB6bfb51031bcc875b1f764df66d98240867624155a65763bc24d5fbd22638db9a
F1 elpis-light-mpw3 7576×111760, 53880 3.1 MB8d2d65fe81cc3893f94a20dcc769485c0ce721ef1de399ba5b094df69c9d3fd0
F2 vsdbabysoc 7576×111767576, 53880 1.5 MB31faebdcaff8ec52c43c8d07da882ba3373d1d8bd725334b305a736f9ff5754c
F3 vsdmemsoc 7576×1117615152, 53880 1.6 MB4549262741338a1c29c2964cc338d40049fd3b9a3555a6c60074286cfe7d70e3
F4 caravel_sram_test 7576×1117622728, 53880 1.4 MB0324be96fc975a2888fdb6571d48d8755effc0f34cd731ef466da82a397f0ec3
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 1.3 MB3d8725175d9deea565d6bcaff59d572b9b642523bb3d40eb77b3c1e62178bd69
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 1.4 MB353e192ba6f3c5c604caf2c4e03f8328180f1b75d0fb346fd1a338bf21944076
F7 caravel 7976×1117645456, 53880 1.4 MBc77f18b819b3d76711cf60fe811207655f8775eb977bc48cf2c43504247bd1b9

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 VIM on mpw-003

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

Mask layer
VIM — Via
Process step
118 — Via1 mask
Drawn layer
68:44
Layer on the mask-layer GDS
40:0
Detail
in the sky130B RRAM tier this is cviam, the lower half of the split via1; the upper half is VIMC (r1v)
Also
Via 1 (M1→M2)
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.