mpw-004 / MM4 Metal 4

the MM4 shapes of all of mpw-004

40 of 40 dies rendered.

192,777,311 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 (307.0 MB in total, largest 11.4 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-004_MM4_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-004_MM4_reticle.png
the stitched reticle, full resolution
133.4 MB bd8756d91ba73f58c2b578439b55a655dd82eeca1a2026a0e6c32df1d89b0a5c467b3b2c 07887c5064b31559347f58c7cccdb1207b8098cf645ad39be68e740bf7210dfc
mpw-004_MM4_reticle_overview.png
the same image scaled to fit 4096 px
5.6 MB 254557dad0ab2dc4ad871f0822740f4713dcc249d4587c67b0852260ee34f4051c2e896d 2c15d2f4feb4187a97f97b4f5f766f606f3e50a995f6610cb5d552857cf8c12c
mpw-004_MM4_tiles.json
where every tile belongs, and its checksum
13.4 kB c1d14536fa356018baa3e550fce51bda9609ed4f15100417d2ef920f2165a1ec250df2c9 69878560bd2a150589bdb60184d2cb3582c06d5f827c76a1538afa68110b17c7
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 zero_to_asic_course_group_submission_mpw4 7576×107760, 0 11.4 MBfdff21badae55d808a29641cd683a31bfeb84c49afdcead781ae7a551ac1e47c
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 11.2 MB13eaecfc52c6ac0f15f5c6131f444e1558ae15ce1b2b286d829795c3d0b61f1b
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 3.3 MB01a5c9c63425dc09088c91496a689a07114c3f3b6c84c20a531c2063fc734729
A4 pifive-soc 7576×1077622728, 0 10.2 MB66fa80eafb3e2014b9e9109cb71b52419b2aa3da8bc6e3e7b5a312358cd58530
A5 ram_generator 7576×1077630304, 0 10.2 MBd41915f3b5261739a00f0eebd0f86e48a8bd32536c69597d8cd1b8f15b5b674e
A6 space_controller 7576×1077637880, 0 10.3 MBe7685c451114587cd514824a9deab04089c021bb62eee098d1763826d52b9d8d
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 10.3 MB91040f5c6c25312df62c41814fbe873c05945ad48f5518ed1f16331adebf751e
B2 4t1r_testchip 7576×107767576, 10776 3.4 MB7433f695b7287e43d10de86b5fcd911a251b532eba11783482ac6c930c0eb2d7
B3 yonga-turbo_encoder 7576×1077615152, 10776 10.3 MB2eebcb208abe953dd09991282b8bd9d869eb65e5c4fc1b261a6d451afe58f454
B4 icesoc 7576×1077622728, 10776 9.9 MBa4b66208a979b7dccaee730ce51845fb8cf6489835fcfd1e7c4a99df288d74cc
B5 key_value_store 7576×1077630304, 10776 10.5 MB339082cd1d05e74dfa87e9d4197a3e601a0a4bb1891404fac7125bcf1c40a999
B6 subservient-mpw4 7576×1077637880, 10776 10.3 MBaa3ff5ea93762e8e88d27f0899d0848173e98ce0c1312924e8bf6ba157743e7d
B7 logic_bist 7976×1077645456, 10776 10.2 MB9468b6f5635753f9f788fdd0bff0b6e4a2e7f9468bf461c452131fc37eb72de3
C1 riscduino-r1 7576×107760, 21552 9.5 MBac1cd66ee8b77a1d2afcb89a03b8e07ea47f0b1dee1134e72efc167efb74cc2a
C2 template 7576×107767576, 21552 10.5 MBa8925050bdfc44ba9a3b044638a25d1c9e0934564ba113b62f26b200288b1095
C3 vexriscv_soc 7576×1077615152, 21552 10.4 MBa594cbb012eea2d9d351d50bde01dcb624c3976711e699cbf8be39bf8d318746
C4 ring_oscillator 7576×1077622728, 21552 3.3 MBca2ced272c8daf01a160fdeac6ae60383abf6b59b0705fee83b7e25a9949a469
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 3.4 MBf1559ad1dc692ed95cd1a37b703fb2219f64ef1fad404906e2ccb39071ffa92e
C7 approximate_multiplier 7976×1077645456, 21552 7.3 MB4141b21f508dd8fa3f382128abdb3c10db74948321b5c9fa1ebd517257b1c9cd
D1 icd_fast_nu_mpw4 7576×107760, 32328 3.5 MBb8280bc736f91c779a0d752c3079bd6e7610b5eb743d86cd2fabf147a15f0e1d
D2 rram_testchip 7576×107767576, 32328 4.3 MBfdc3436fa4a289779d2222d8f8e8ac2d97621ddb9657c7e8f9f5b27ff3b323c6
D3 rest 7576×1077615152, 32328 9.8 MB0845e7ea0faf8397e195d0e6947e4eb78a2f49769af76f1cecd562cc16aa9516
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 8.2 MBd53033909e9cd2296dec1a53ed178a02184dec53572f00b8adb3d92f21d01c5e
D5 sky130_radtol_test_chip 7576×1077630304, 32328 4.4 MBf6e075d735fe14deb680dd70fb1e5bc57c6a1a6b8a4d92a707d9ccbcd8d241f8
D6 two_stage_cmos_opamp 7576×1077637880, 32328 3.3 MB97836e995457009c6e9b8dd165a6b83e8b836eede57698298de4a8386a320b54
D7 ks-guitar 7976×1077645456, 32328 9.8 MB87963374b57c507c45dcd4f4ea03a1d42e489e52fb02a5006154c0a81e256fc1
E1 ks-guitar-2s 7576×107760, 43104 7.3 MBbf93c6790e3753af750ba18c36ca6ba705b59d34faee401f1f8a4d2d6b24351e
E2 yifive_a2 7576×107767576, 43104 9.5 MB014a0ccc2687903c0ebde7bda5afcf9cd9656e766715e83927126ec334bb5828
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 6.3 MB4d9ab0884a2bd4c9331e788b594cdfa7f647a76a923405c6f98f7b9af3e8e692
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 3.4 MB28ce19a985e00ee2ce2204487eb121b4a6c0254e0d0e95c29571eea1b87beb9f
E5 junga_soc_mpw4 7576×1077630304, 43104 10.4 MBfdf9cf95f3234aa9adb28305a669aa32dc792177b601395d3b47126a2450a1be
E6 ibtida-ii 7576×1077637880, 43104 9.8 MB3f7eb0d4cf2aa88fb33bb37d16c532f4ce653ef5581cc2a4e12fe27cc43f0b2a
E7 azadi_ii 7976×1077645456, 43104 10.1 MBf26c4a883affff900efbd9183ae53802002e5b4f2c65b8d6d7fc476ae9cbd814
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 7.9 MB70d1edb2c01755c12ad9f1837cc08dabe0c9f3deb9a3bc99f6361a031ed5eebf
F2 current_starved_vco 7576×111767576, 53880 3.3 MB745fe18c8358317fa85737b207b99a0f8d5cc60099c700a3067760105aac6da8
F3 updown_counter__test_ 7576×1117615152, 53880 10.2 MB029a5d4fd8773105de4723f99afccf8a974091e470f075be9e4c8333ca34d85f
F4 skullfet 7576×1117622728, 53880 3.4 MB62db74896b077a4f4566626c7e5445500b794cd998c99d22e0336ac968287058
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 3.3 MB9c86308fd7ab4666c372b0b8fae3ab674be405390dc538f41b93ad7370388095
F6 kasirga_k0 7576×1117637880, 53880 9.9 MB47c9ef5d38d6bc2da698faea3f6dbe82adc92ef775d2023f4fd847eeeda35618
F7 iotestvehicle 7976×1117645456, 53880 3.3 MBbdcb64d6bf192e11b114c808a79805087ee55a372cfcbfe535d7bdd281e9d8e5

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 MM4 on mpw-004

Resolved: reticle 5CS8010AC, run mpw-004, mask MM4

Mask layer
MM4 — Metal 4
Process step
154 — Metal mask4
Drawn layer
71:20
Layer on the mask-layer GDS
51:0
Fill layer
51:28
Also
Metal 4
Used in SKY130
yes

mpw-004 — SKY130 MPW-4 (original)

Foundry product
EF MPW#4 (+ 'With ReRAM' split lot)
Reticle set
5CS8010AC
Run date
2021-12-31
Submissions closed
2021-12-31
Projects
52
Fab lots
4216266
4216266
4216266
Identification
confirmed — Lot records: EF MPW#4, lot 4216266 = 'SKY130 MPW 4'; the set is absent from the 2026-08-25 return shipment (destroyed 2025-06) — see 5CS8018AC
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-4 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-004/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.