mpw-003 / MM2 Metal 2

the MM2 shapes of all of mpw-003

40 of 40 dies rendered.

528,686,022 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 (524.7 MB in total, largest 20.6 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_MM2_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_MM2_reticle.png
the stitched reticle, full resolution
236.5 MB 2c56d5eac19b4ec971187ca07ecf1cdde5ec92733cd619cdc419c2f86ead7672324c9dbc c56c8eb4c7b405906ffc50bb6803fd094ad7432f634918a5a9e6ef0fa59d31dc
mpw-003_MM2_reticle_overview.png
the same image scaled to fit 4096 px
5.8 MB 3c76ef039dcbaa64f4576f09a9f9af5eb88e30ce94668c3ac9175015b7b5c40b38cb161b 01915b68ab4eaa369dff9e87a0149ee9c464da30dfdefca500bfbb1316392024
mpw-003_MM2_tiles.json
where every tile belongs, and its checksum
13.5 kB 8b19dc3cad2ee0c697cb9e9d2d0ef885e2ee5cde380dd5547ea6b69331f916be6ae913e1 aba01325e8596de05d2b3f89064f9a3748153f60273ca41588ba704acff4a5b9
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 14.9 MBd24eb0455ed3837599928a608ac2474c45f29f9ff554ed21e6a809629e0357da
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 7.6 MB4e97d18253ec2d78f36acb7e9f5cffb9bcb56b4b0aa42d27e6e8c213a1761360
A3 openram_test 7576×1077615152, 0 10.7 MBe91ea0e2f611ab60b937c0bac6bf6ce91ce4e81d6f210ed8e38748772fe7276b
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 17.3 MB7b03fd80430c9e8caaae1545b1c7eef17293510d2cee0f5bd84cd2a4682970a0
A5 crypto_accelerator_v2 7576×1077630304, 0 16.3 MB04cecaa72ba9a62edb606a10cd2eb18bf3d4dc8d23e4e73de0e1c6f079826173
A6 picorf0 7576×1077637880, 0 15.3 MBa434eeabd5a149c96d85272e5821a203fd859a18818c504d1c24c04db6fb48b7
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 11.5 MB0afb8e59af082fee143ce3de6ecbad005a37feceff7dcfa15ea51f191c4aea7f
B2 yonga-100m_ethernet 7576×107767576, 10776 9.9 MBd1337a718f63698d67a6bd3853998655ce3141dc9529618fbf6928af41f80827
B3 approximate_multiplier 7576×1077615152, 10776 14.5 MBcab2148331c05cf207b2cc58c23a2fc4fdae9153938ebcec339a2fef4d2456c8
B4 vsd 7576×1077622728, 10776 10.1 MBbf0715011d4d01e76401554389051f1cd9c52e35bc5a24007ecd793dff203452
B5 asic_key_value_store 7576×1077630304, 10776 14.9 MBd24eb0455ed3837599928a608ac2474c45f29f9ff554ed21e6a809629e0357da
B6 mbist_controller 7576×1077637880, 10776 14.6 MB746b67cbf0ba3dd075ff597ebda1ed11e60bfc35297cd7229848fc571c7af98c
B7 riscduino 7976×1077645456, 10776 16.4 MB60de3f116a67e4c8c7f67ae4b3c19b61e465d366d695bd19d0dfe0503882d75a
C1 caravel_peripheral_extender 7576×107760, 21552 16.3 MBdbc877b75685dbde273b6b98bed18e92a8730dc741b5d951c1a05f1d2ba1aa2a
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 14.2 MBb0079822013f312f3ff32ebf5cd10e421547ee357004170326096f7e19872709
C3 class-d_audio_amplifier 7576×1077615152, 21552 8.0 MB2482aff05ea369fddf41cacc29b2f5979df3d61d4f6e22c6b84ee7b4224fa865
C4 efabless_processor 7576×1077622728, 21552 14.9 MBbd1ea57d3438b93bde5a8be825799d95835f591f250e79c5a3f3866ad020c326
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 14.6 MBddfa72c5ae865b542b65a7ff41b542d5d9c0a7b20473b81be07d3532f32f8597
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 7.7 MB9478ce87c3110075cb7a7f51d198c8abf26ff4532d7e478780051e6b93b1310e
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 7.4 MB85520f997e46f54662d6ce126ee834864d582221075d706b1b5f03a085672a68
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 7.4 MB480e97d40bef2c2011de9b01416fe3748dc94c9a26765e62d479cb862606a639
D3 sziklai_pair_amplifier 7576×1077615152, 32328 7.4 MBaaf781e38c2ea08ef2cdde806eee782447485f51bdc2d69d925ce6b51e929bec
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 7.4 MB43a1beb5b2617a675a34f6df69fbf6f29a7dea66f6ecf0bb18c3511999f2877f
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 17.7 MBc25a1037713b3f7255b18177d92370df0652bc8292365e5d3bf3e732544235f4
D6 rotfpga 7576×1077637880, 32328 14.9 MB38e5bdd97b98e9a265e388a32da5c206a2a446751345b1960fe18e66e75f4cea
D7 treepram 7976×1077645456, 32328 18.8 MB436455e9e312da9ed7c315647610f80c743d923fd60d076587b751d69421b460
E1 treepram-red 7576×107760, 43104 20.6 MB5ad9da8095a55ee5c5358dc3a66b059f011c0560a850d4ce299e65eef73984d2
E2 caravel_jacaranda-8 7576×107767576, 43104 15.4 MB7f1dc2d2f4be8e6b0e00c27c4a297a096191db200f1ad5d3eb70c0704fc25156
E3 sudoku_accelerator 7576×1077615152, 43104 12.0 MB08163c77d915b4e8e6c5312439de3600301be5746af02e6b71b6da0669c20dee
E4 fixed2float_converter 7576×1077622728, 43104 14.5 MB36882b64f051707395d5475356f8b6cf959aea10213496648f00ae53a2225737
E5 high_speed_adder 7576×1077630304, 43104 15.0 MB0794d38c58895622bddeb8b3521401532deaab26e16a551b1c82c770054314b6
E6 my_proj 7576×1077637880, 43104 14.7 MBcef3bc76d4212438b8878287aa702b00f758f8bfc6d45418120a89242ac62fcc
E7 pwm_test 7976×1077645456, 43104 14.7 MBb682c03c64f0f653440a5149008f36a45d72a63cd82f1df73a50e46a9046d225
F1 elpis-light-mpw3 7576×111760, 53880 18.9 MB1cf7fcd11176cc63ab9130a18325342bdbb0fd1215ad54d11857915f24cea078
F2 vsdbabysoc 7576×111767576, 53880 10.1 MBb98ae27db4bfc788be7ce8ba177d75a89e3aba48aa8474ec2bf77dc1a91263da
F3 vsdmemsoc 7576×1117615152, 53880 11.1 MB559d856ca19e27e303800112914da63679a074aa07457819420f29c825d1d5d8
F4 caravel_sram_test 7576×1117622728, 53880 13.9 MBb60755f66fb6eb696425bc810f7b9f0b003213e3740c5f9760dd55b4e78357d8
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 7.5 MB22464e2cc8f36239ad107e6a58abe0ccec1cf0f61bed67184f3fa39c5ff34d9a
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 10.7 MBabfebbbbd7bf4682ae4061d9c3175d63a7d240dee9be9e8aef91b205ce88a561
F7 caravel 7976×1117645456, 53880 14.8 MB697eee8e8211167b0cdc87e7e43d500dc328ca2a073e9c42205e3c660ac9f66c

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 MM2 on mpw-003

Resolved: reticle 5CS8008AC, run mpw-003, mask MM2

Mask layer
MM2 — Metal 2
Process step
124 — Metal mask2
Drawn layer
69:20
Layer on the mask-layer GDS
41:0
Fill layer
41:28
Also
Metal 2
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.