mpw-004 / MM1 Metal 1

the MM1 shapes of all of mpw-004

40 of 40 dies rendered.

656,523,198 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 (262.3 MB in total, largest 13.8 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_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-004_MM1_reticle.png
the stitched reticle, full resolution
122.9 MB 0955b08bd5f7f7358bd68a7610732c5c0f30d7cb798905555da349066ec52075be10c528 e11c84bb46155884e9a628fc0ed767fad5ce0ee7e90a64ba93fc001818facd7d
mpw-004_MM1_reticle_overview.png
the same image scaled to fit 4096 px
4.8 MB 375a348008fe0b41601af5cfb5f88a1c9600350453d0e9d3bd720583b36a4cd243ba4561 3c977f53ae6e860b109d9f1a1864b5f93c669248c55828f657648a6c85bde33e
mpw-004_MM1_tiles.json
where every tile belongs, and its checksum
13.4 kB 6efafac9ef96b30f71c283b9a4086633309927b43989eb4c103e78fe3462002d84491a95 48cce9692492530973816dc77e2509667812ed3456c5dd7bbfd94914ffbad05b
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 8.1 MB04ade96ad25bd631b824fb6b40d137e6798da9b355a70e41ceb3d8740965bc21
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 6.9 MB5e5ee412781504d62a0c4280bd861c6cdf7c28938fa5b384ba53a2047239fc67
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 4.8 MBe5d0a0088323286ec378944a9d0d22c848f356a898ee9b218552519d5e256339
A4 pifive-soc 7576×1077622728, 0 6.6 MB03779cb6c3f7ec821666f6fd9e1715b6a4526997f7cb7f258a849629031b4a8d
A5 ram_generator 7576×1077630304, 0 5.6 MB54fb4423dbfb488653d4790641bf36f236b01fb77948d4b7050c0890edc4c902
A6 space_controller 7576×1077637880, 0 5.8 MB1844e5ff22cc3fc8290ad41d0a8bf98efd2e3372f37d11b13b2593d6ffd4243f
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 5.7 MB49e1d7781ce6750cc58b1abd1be0ee2818da8d18a390146ca67352425e8a100a
B2 4t1r_testchip 7576×107767576, 10776 4.7 MB5ef03ad3b695b41dc4ed0ac0cced40eb7671b19436000423b6fcefe7f5390d7a
B3 yonga-turbo_encoder 7576×1077615152, 10776 6.3 MBf3ed5e75e0f348f20b298f865cae1f91dfa37b5e405ea0e25a01d2ac57d0f170
B4 icesoc 7576×1077622728, 10776 13.8 MBa54776b06594977bf8e9463d92e3f935d3de8745f5f3d0d4440a2108bc01eda6
B5 key_value_store 7576×1077630304, 10776 5.2 MB01747f3b1d69f0aa51e1932da97e97ecd6eb69e57574b6ecbe6189b78ddcd46a
B6 subservient-mpw4 7576×1077637880, 10776 6.0 MB6ec714eaae92c9985207eaf3c37332a1345bff2a5c6cb7fd072539f00e031c76
B7 logic_bist 7976×1077645456, 10776 7.7 MB2aad44784eedca1fe7cf799640f71c61d93c0eb30fcd6a2baeac544fb47aa694
C1 riscduino-r1 7576×107760, 21552 8.6 MB87f5b72c493ab23c20ba9a64568152286bf2257d73e9c9d42c3feec7dbf4d388
C2 template 7576×107767576, 21552 5.2 MB44dc1223d7a82cc4718f383edbb9bb0d538e2bef98ff8185d0c1ec7c0424d9f0
C3 vexriscv_soc 7576×1077615152, 21552 6.3 MB7c923ec4e3579dde76a51cfadb61c5cd15674ccbef301a64bd1b2dd10047dcf1
C4 ring_oscillator 7576×1077622728, 21552 4.7 MB0d76e7b66e4fad6ea5b12650a7202ca34fcfb882fad55a059d607eeeda79e7d0
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 4.8 MB5de55c880d4f8f3386c25970266906068a7a0800500e2bdd8a232f19f5dbd626
C7 approximate_multiplier 7976×1077645456, 21552 5.2 MB3f2f45caf7137ec80873712fc5adbef5af09a53a1b8eb41d92a5967a43eb8078
D1 icd_fast_nu_mpw4 7576×107760, 32328 4.8 MB5e8f0d965175c25a6d4553da934eeb79bf4690489e4b899fde8f22dbd977e4ca
D2 rram_testchip 7576×107767576, 32328 5.5 MB73fa98f9fddba97ef5f4106916773b1d95bf4aba59b26275d9b4bf4af07e5068
D3 rest 7576×1077615152, 32328 7.9 MB333dd6c456c2684dd676b59e729207533fb2c5fa350a27716f7373e56b5598f3
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 5.1 MBfae5a961ae2a4603ba5877af02c4ff90a9266dba5df12a54f9eaa6718a32314f
D5 sky130_radtol_test_chip 7576×1077630304, 32328 7.9 MBc0fa6100820f14217aab4d75a82995ebf5899aac51eb8d36540ec807baab6afc
D6 two_stage_cmos_opamp 7576×1077637880, 32328 4.7 MB421eaa3bd9163d0fe9ba8f367c7b97d148d100291d12aa08f9ce140aaeb74348
D7 ks-guitar 7976×1077645456, 32328 7.5 MBea23f68b764c96a1964409afe2f840eba887fdc1396724f1bf79d9f7b3517626
E1 ks-guitar-2s 7576×107760, 43104 10.3 MB5397e5d6c5801be30de6db2d10eb4cb89c063fb5b7b8f1712ec233141ee94d59
E2 yifive_a2 7576×107767576, 43104 8.6 MBf56e4a264d21b23ebf3dfe307b19d5b2c96e12e3ff0c317e4f8018a221403551
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 8.5 MB11a1025bb6b1ba9edf8bb8435a12078a18e34d522a806a91ab2a76648fb9fa27
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 4.8 MB590c6428323f2d21cf0bd0b3733e961d682e1fca232ddc60a2edea1e585e3862
E5 junga_soc_mpw4 7576×1077630304, 43104 6.4 MB6a3ea716b0ea8ef17c30db36b7c14e2f6cc656cccb521faebf2ad95e362786d1
E6 ibtida-ii 7576×1077637880, 43104 6.8 MBe7c849262a08f4683f933c9b4807fc16f31d2cbb800b03dcad8db571a6eb1121
E7 azadi_ii 7976×1077645456, 43104 7.9 MBe193badb8b83fe51c8b8252757ec7ca83c52a47dfc7aa59258dad4771024a7b0
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 12.8 MB4b442a2c403e192c3521423fae70d836432862c05030132b006341c34fbf4e0a
F2 current_starved_vco 7576×111767576, 53880 4.7 MB5eb12f13a434455bb8c61c67d63665a51c3eed887653824db6c5329d20d4cbf6
F3 updown_counter__test_ 7576×1117615152, 53880 5.1 MB6e5149ce1ed38854be2041573fd1110a50a29bf9a8d9c706eb0df171a3aa1921
F4 skullfet 7576×1117622728, 53880 4.8 MB248e86355e9bdf83793fa1fd1a2fac5b40118bb1c02d95c418dec40138b89b8f
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 4.7 MB7064a444df05e4932a3d61471a54aeb24eb0e5c4ba8ccd65b5b53ef9f7ba96c7
F6 kasirga_k0 7576×1117637880, 53880 6.4 MB55d7e8bbf7037363ae5c73e4da855e42e3eb008fb4cc11fb950687597bc20727
F7 iotestvehicle 7976×1117645456, 53880 5.0 MB623ebcc4dd42ceb063c07d5b3d929ced97f81694f742763ad48ee942914c3401

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-004

Resolved: reticle 5CS8010AC, run mpw-004, 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-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.