mpw-003 / MM3 Metal 3-PLM

the MM3 shapes of all of mpw-003

40 of 40 dies rendered.

184,137,262 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 (144.2 MB in total, largest 5.7 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_MM3_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_MM3_reticle.png
the stitched reticle, full resolution
56.7 MB 56bfd3c1287d8e8f069ba115fdcc2d0ec529847794a9cb29d3232fdf801f6e295e097874 63da42dec17c7e3a64d1940a4137ee9af254452aef7551bf57c5a8c0562a984f
mpw-003_MM3_reticle_overview.png
the same image scaled to fit 4096 px
4.5 MB b5b6bfb98be3cffa97a131579f577aacf6df29397d45c59e1db6135d0b3947c60010f77c c90a85dc06be1b80930ec5d2961aa0c40d698d570aeb864929b4678c7cf24253
mpw-003_MM3_tiles.json
where every tile belongs, and its checksum
13.5 kB 3c26d4cfe53ffcad829ad7249728f16ba1dffa33d18af94c8dd96013088b14cf5920ed9d 417dbb9757f648d9250e21edcabb34a10bd71678728874444c9abf7027236cf6
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 3.3 MBd127ec187d7dac7aad97215829e416dc935a294267d1d90eb1ef0c5d31633071
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 3.2 MB28da7335e5e3c100dfae02791833879f855c8aec8a957527f4a8daa574920f0e
A3 openram_test 7576×1077615152, 0 3.3 MB0059bdb7e840b5d2035c7c368ea8ccf7d6b68d875401123443d2b38cb845d04a
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 4.2 MB12f5e0d83c2053b1ff39845661ed6e6c1e3196158313f3b464be1144a244b192
A5 crypto_accelerator_v2 7576×1077630304, 0 3.8 MBf4523d47d7ebd395ca1a31c2b2e76452c6fa2afcd55b4c281dc0d59b6d7dcc63
A6 picorf0 7576×1077637880, 0 3.4 MB1a6c62c1ae269f5868e4c9bcf73124a98dce5df5e7eaf752353a4d40b3af0be5
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 3.3 MB8410554129b0f762fab4115a2ce74ba88abbfe883c38ba947c3e256f5a590ffe
B2 yonga-100m_ethernet 7576×107767576, 10776 3.6 MB27ab1d55319a0fe146a54d8463763f6912741746f4a08be023696ca6b54724a0
B3 approximate_multiplier 7576×1077615152, 10776 3.3 MB906084f9fb9b0fc3667456761bb1fc7b891f17ea31b881e8cc2a0bed82354925
B4 vsd 7576×1077622728, 10776 3.3 MBa1b290e9cb98866b8face3b9cf281e337ce97a5e4519e1833538d2a1c48c2ca3
B5 asic_key_value_store 7576×1077630304, 10776 3.3 MBd127ec187d7dac7aad97215829e416dc935a294267d1d90eb1ef0c5d31633071
B6 mbist_controller 7576×1077637880, 10776 4.7 MB1c9e4dfb2558ba1a942ac0a287c5ed32b414dab30721344120480fd12f5619ec
B7 riscduino 7976×1077645456, 10776 4.9 MBd98d514cc0e808d650d2679dda7837dec64dc995ec7aceafcfaaf1ee356a3ec6
C1 caravel_peripheral_extender 7576×107760, 21552 3.5 MB070c63bf0b57b18349902688ff2a8411646859150adee12b9e5f7f76fa278ab5
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 5.6 MB7b1fbf114be37db9b8222a44b44ca0e4ff7100b6def653e42c559825d67bb621
C3 class-d_audio_amplifier 7576×1077615152, 21552 3.4 MB30d90cf606b559c51b99b5acd9fb97bc470dbc5db3485ffd4329df186459548c
C4 efabless_processor 7576×1077622728, 21552 3.3 MBb665ea77edfcb208c0c5f7a1e3a7c4f59d416e2166363b463c8f1c7e5e26e790
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 3.2 MBd70c15d996b058ee4cb99b41e513a097eb5003ce83d9b3bd76df52da85dc63c9
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 2.9 MBa54e9795958e63bd3b5d75150137e62d28609274218146b25d4eb431b73eb7a4
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 2.9 MBc4309dd613fe2e020878f296c8e4642d709497fb58adde1f7e15923d45484317
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 2.9 MBca9e2640a4f73d344e404a8c88e65acaa501a26dfef165d6409fa9da8356fa77
D3 sziklai_pair_amplifier 7576×1077615152, 32328 2.9 MB15bfe9d67e98e6fd4783f941dd268d9793987d3631dacf8bcbd3d9377f3ab0ca
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 2.9 MB482082f5914db707c93d4e274c99186e8ec09384870fb1a79eb58eb13b0a4362
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 3.8 MBe7b5cc7f467b85857192cfa5b82fa70479cc30307f6a3bde8167ff1fe6d14541
D6 rotfpga 7576×1077637880, 32328 3.3 MB35ee1e94d9265734b361f69fce363c38bb4dabf6974135f62dfdb3b54bd0f021
D7 treepram 7976×1077645456, 32328 4.9 MBad5776162e6db7e9976c3190d256bba3d471a52796be0f49301dee98e4327a38
E1 treepram-red 7576×107760, 43104 5.7 MBd77d45284ae36527db43c193ad26d3f7249beaf73be4747586c5a1ff7c779628
E2 caravel_jacaranda-8 7576×107767576, 43104 3.5 MB922eac64abccc3e564f6182f0b735967789e0765227ecfb8871d885f729c5d51
E3 sudoku_accelerator 7576×1077615152, 43104 3.6 MB3740c9cabbef835c39601ced5ac6858885b345749a9447e6df1ddc41f7c2e3e3
E4 fixed2float_converter 7576×1077622728, 43104 3.3 MB2d6d19066deab4d8d3dc214fe4c4705f60cd54135fb4740916f7f20a22ca116d
E5 high_speed_adder 7576×1077630304, 43104 3.1 MBd6b2095a99081ac3c65eacd805b4e9513c570185450157b791929c4c6855c80e
E6 my_proj 7576×1077637880, 43104 3.3 MB9584c8b28a4a3c73593bc374203fe3f18f1b68f2f092ba16418d17c3e9cbdef7
E7 pwm_test 7976×1077645456, 43104 3.3 MB78ee33ff15e20a9619343d93f672d43d3eb2b4a02f6fab78863a8fd8fb6f3740
F1 elpis-light-mpw3 7576×111760, 53880 5.0 MB3071ba3d353d1e61cea92ca60b196f397973b83fea18674ee1a267829bf96f86
F2 vsdbabysoc 7576×111767576, 53880 3.6 MB67ecc6c4a19ab86380d1aa6e07df4368c75962e5087c236d48427d43e9e1a09f
F3 vsdmemsoc 7576×1117615152, 53880 3.9 MB1b3899246272e5269821737d800dfbd11995b05d6b3086d64ee4f09a6de31e27
F4 caravel_sram_test 7576×1117622728, 53880 3.3 MBbbe0489e9db3b2422dd7793a13ce99a653fb969ad68f090f21e0252eaa6644bf
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 3.0 MBd3057f667d4348208815c5e89090ea26e1ee2894895cd0df12abeaa2f055a08e
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 3.3 MB7a07c9269d6c683e8d4583be8979aaf28d3be4fa2394e9134d7fb85b5528436e
F7 caravel 7976×1117645456, 53880 3.3 MBebdcad4beb96bc58f2190cf799201dfc16b0f30051c2b85004c14c5fc9fedd17

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 MM3 on mpw-003

Resolved: reticle 5CS8008AC, run mpw-003, mask MM3

Mask layer
MM3 — Metal 3-PLM
Process step
139 — Metal3 mask
Drawn layer
70:20
Layer on the mask-layer GDS
34:0
Fill layer
34:28
Variants
Metal 3-TLM, Metal 3-S8TM, Metal 3-PLM
Also
Metal 3
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.