mpw-003 / MM1 Metal 1

the MM1 shapes of all of mpw-003

40 of 40 dies rendered.

640,393,448 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 (240.7 MB in total, largest 12.1 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_MM1_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_MM1_reticle.png
the stitched reticle, full resolution
98.0 MB 55d56812b559a4f95ec848f5957e8ac535afff1779b15a14e14584ce5ec4b702c387f0f2 e0029965a4219d7f44c053e143ffbb06ed864a3a5ed5ab69d64bf66e8b796141
mpw-003_MM1_reticle_overview.png
the same image scaled to fit 4096 px
4.6 MB 94dcf7e867499ca4b6f3707901056d6fb3de8fb26d6d14e3761982f5d3727ab9d359f9ca f7589a320e813aa64fce706548d73d5ad264a359f203760f583d7b6e50799b27
mpw-003_MM1_tiles.json
where every tile belongs, and its checksum
13.5 kB 3b2f0a594cce59b08bb6b92ad360df9b3194cca3f29d43d7462b5778225412b1d988b891 000997ed670571efd7a7109eb7316cfd306958961c20d120fc46a6b838001069
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 5.2 MB3bb120f351bc3d3c42e035e84e6fd0fe9bd4e36c14a747d99fb88e13d2b0829e
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 4.9 MBfc6446d7fdfbc9e162d974dd4fa03fdfbceb50f57c457735019b3436db18b1b4
A3 openram_test 7576×1077615152, 0 5.3 MB2c52008646308c60f74f694903d137ec189d9a018beeb13e73d1138e47feb74d
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 6.8 MBadbcfcc3495dfb6ce956a2a7dc73b90ed5977f06fd38f1ea53e770d1ad5efd97
A5 crypto_accelerator_v2 7576×1077630304, 0 7.0 MB46a8593937221b2a1b0e3029a9fa058b5fa121ab4c57a5804a7c41b7e8de4003
A6 picorf0 7576×1077637880, 0 5.8 MB1e59ad86b5dc0b9b29ad134816d43e75a37ae9c1a74196e347a9347062ceeeff
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 5.5 MBa1abdc60b7a20c8c85226dbe951d59c5df0b75da7a946a9a258c8bf57acfb749
B2 yonga-100m_ethernet 7576×107767576, 10776 6.2 MBa9840ff36db9c7a9e6fa6768dad3262fb713b4be28e0b2f4a002de62a868c138
B3 approximate_multiplier 7576×1077615152, 10776 5.1 MB2ed6972987d69cd2a27445a9bf2e75fae506d66eb5d90c5f2630a4e8a7a6f67a
B4 vsd 7576×1077622728, 10776 5.2 MB2f9f56f5ff44f738be8ef400b76f0689fdd4e6578e26e9ea55799b73b6ee6c5f
B5 asic_key_value_store 7576×1077630304, 10776 5.2 MB3bb120f351bc3d3c42e035e84e6fd0fe9bd4e36c14a747d99fb88e13d2b0829e
B6 mbist_controller 7576×1077637880, 10776 7.4 MB07181f87f2214040c295e4ad4bbc951a554f6e36f01acc29587b62c11074c79f
B7 riscduino 7976×1077645456, 10776 8.5 MB9908bef6ed0e47e04e1c7505725668413cf43a77610a113d7906799dcdd019ef
C1 caravel_peripheral_extender 7576×107760, 21552 6.0 MB2b47fbcd546f53e27b83a3b7039c4ff2162bbb84b869762c8d546cb1e6db70ce
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 6.9 MB0d7f05f3e8489599156c4d0ae395702223e192310bd6e791e069d0dd95df942c
C3 class-d_audio_amplifier 7576×1077615152, 21552 5.0 MB517a81cbc291d9f2256cdeb44fca31d75a5877c1c43f8fd9da4738eb1f885868
C4 efabless_processor 7576×1077622728, 21552 5.2 MB928f42f7ecc76f3b5135a5325d987a7ca9e43998879e5d1f38c03ff6e7e9ccd0
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 5.1 MBa004ae030837971b89ac688a1e2cd21096d9e379bafcf3911080d136bda8142b
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 4.8 MB41f9240f36c8f9bf9a43848b4db661a8f3978583f196107d8f1abd6ef6c65b6c
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 4.7 MB8bf8b8985c3a647ea785a73503bcc9d2940c092fbb1c7ac7431d0f962bde8acf
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 4.7 MBdc44026128cebc93a727b959282bc149a43796b13afa21310f4c74be50017793
D3 sziklai_pair_amplifier 7576×1077615152, 32328 4.7 MB8d4394551db87c3ea2687eee1fc8a2edd93ba589906176909dea30da7333b37f
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 4.7 MB340fb0a54d9640374188d746339cca0d3bf40c76fae6625e436a0cc7c10bf757
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 6.7 MB194ad72fe1064d9ede0bd5f423ca668978b3880deb27ad665397cfafd7f5789f
D6 rotfpga 7576×1077637880, 32328 5.8 MB76ef84465201efbdbccb86ed6ac3fbdb91331fc422a2113a37acf23c7e1c4d1f
D7 treepram 7976×1077645456, 32328 10.3 MBaa36e1373ff333d28124bc79622776b35738fe00800a796b1d6ee35ba3e71f2f
E1 treepram-red 7576×107760, 43104 12.1 MB58492f3582b3c576944af18db03353768e672a47e678e4bcc2cb140dabdf66cf
E2 caravel_jacaranda-8 7576×107767576, 43104 6.0 MB0731aa8dff587bb011cf5432dbaed5acc692494e763adfbe7723b0a979efb812
E3 sudoku_accelerator 7576×1077615152, 43104 6.1 MB418efbfc6a1c7c10e646db889655d74f48b4947881fb396bea351103baf3f061
E4 fixed2float_converter 7576×1077622728, 43104 5.1 MB9b580db54467aaf0e2daa93ed6d83197e806059eb7d42beb91e6180b7a01591d
E5 high_speed_adder 7576×1077630304, 43104 5.1 MB1ea0946b384b153c6fc438adddb30380fc41e841d8cccda12db42cef0f8345df
E6 my_proj 7576×1077637880, 43104 5.2 MBc3de7d3d8fc57c5c766249e93d0781616fada1227dd00b253f89d0789b457433
E7 pwm_test 7976×1077645456, 43104 5.2 MB5852f28a818b6244ad9498c7e6a62c8328f6ec2dfc7dcfb3284b3081c1afc6da
F1 elpis-light-mpw3 7576×111760, 53880 10.3 MB86610a06215e57f511aec70a460e5d30a84537a1683e06766971f4b248843069
F2 vsdbabysoc 7576×111767576, 53880 6.0 MBc7a27071d455dd7b9752f7863290524f1e3d55a3875d5fff3a754bacad231bc1
F3 vsdmemsoc 7576×1117615152, 53880 5.9 MBc3ee5bdd58970f1704c34bdd4a45f744aceb413e23f27d362b1e91af3ba758a0
F4 caravel_sram_test 7576×1117622728, 53880 5.3 MBacbc78e6c0d8b79eda69c4b7a64434aeefb717f29e24ea4d1276960445efcc21
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 4.8 MB6f2bdb629f093c0bde57042632849ec817536399c6581a127a3d615c58f6ee07
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 5.3 MBacd47ab681423b72260801c6c4867cbd71085f43b9226c82225a26a488ef7a6f
F7 caravel 7976×1117645456, 53880 5.2 MBa79fdc75643a4720dd341d1bf8b79eb47e3277f29c1450cdf128351f31bf5494

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 MM1 on mpw-003

Resolved: reticle 5CS8008AC, run mpw-003, mask MM1

Mask layer
MM1 — Metal 1
Process step
113 — Metal1 mask
Drawn layer
68:20
Layer on the mask-layer GDS
36:0
Fill layer
36:28
Also
Metal 1
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.