mpw-004 / MM2 Metal 2

the MM2 shapes of all of mpw-004

40 of 40 dies rendered.

517,083,731 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 (496.3 MB in total, largest 20.9 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_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-004_MM2_reticle.png
the stitched reticle, full resolution
244.2 MB 4d1ddd2063df4cd99491263d24c305531b31c32753fbd6f0f9ec889b47272f551cc075cc a4cf583d254458b5083858d1fc9a95c267ea69191411af9ff984b5003260d332
mpw-004_MM2_reticle_overview.png
the same image scaled to fit 4096 px
5.7 MB c001047f0778671a4608aba26242510e8fa7822d7037ad1a4faadfed36ce1cb868fb2337 fe523a753a744826f59f9dff46f6de2fcc7492f62841b418dd939158953631df
mpw-004_MM2_tiles.json
where every tile belongs, and its checksum
13.4 kB 0e3eccdc98b81c74d59882c7dafc9a9a7d9c5978f6632c52afd8f30b9345b4c04fa695e0 9452b559dc5c61f58b57a72708dd95066be6291cf8307f5bc6867408d020167e
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 17.9 MB6daa1946b63ab974699ae5dd30dff9ffd6cab27cfe661411a4beab87c8ca6c4f
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 17.2 MB6e4024f5b54f8b69740b868904bc89b444e44183a518a76a449ff6ff876ea7fc
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 7.5 MBb52f57d608e84806d7e8d38a4a2cf7650706538c9652fac67e7ee94cdcaf3ba3
A4 pifive-soc 7576×1077622728, 0 15.2 MB6a443586967c2852d927bbbbdd8c5b970ace6a9417031438beb16b9c5f220121
A5 ram_generator 7576×1077630304, 0 12.9 MBbcb4349f715a391b3463081ec36db3a6833bfd096235402a33da76a8e0718d56
A6 space_controller 7576×1077637880, 0 13.1 MB5c0a3195d928ac5049af1b70d8b565665262163ba05a2182ccbbc7cb6c9471bc
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 12.9 MB589d82d584653acbdf11797d114ee16185158b19305ce77e74544e0390dd1d12
B2 4t1r_testchip 7576×107767576, 10776 7.9 MB2166555145d46330d914d53da1a48b576a58d98c8ded9f4feed192a7ab73483c
B3 yonga-turbo_encoder 7576×1077615152, 10776 14.9 MB1cd588eae5d025e6c0ffecda9fcf5539e0f463403a90492c209f4cd40ee82ca6
B4 icesoc 7576×1077622728, 10776 20.4 MBc4be453304d43af0008e9a159999fa6cdc8b1e40012146ee7fea6289670295a5
B5 key_value_store 7576×1077630304, 10776 10.6 MBe84f9b6ca274adea5574ef7f589cfd35d1a02afef67365a19f1c2a3b91f1ea39
B6 subservient-mpw4 7576×1077637880, 10776 12.6 MBfa6d75478429e544aa1f29ca04d1827ee13cd02ac41da5b64494cdc488e72371
B7 logic_bist 7976×1077645456, 10776 15.0 MB8dbfa52253b929a3ace793a3c7cdc297e5899c1e1e2ad1c15db3e3916d380da2
C1 riscduino-r1 7576×107760, 21552 16.4 MBe96c8cf03dd0fb9df7bf6a17c57b98af01e4f27f86cc9992e95c29572c83c357
C2 template 7576×107767576, 21552 14.7 MB3c8891e8ece73972e12b6599be62f0503af625d27d9ac5fa9571bfed0df53299
C3 vexriscv_soc 7576×1077615152, 21552 13.0 MBab4be3212eb8e8ca0d684cbcd40a565d10a8fb110e4d518ab121f286fc8e7de1
C4 ring_oscillator 7576×1077622728, 21552 7.4 MBc35b6a7285bf917dcfab60dfdc392cb984be5f8788d6b490a636587063226ae1
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 7.5 MB931dd0a8b31112c77049ce731ee786527c907c7567a2985a2dd9d28e613fef95
C7 approximate_multiplier 7976×1077645456, 21552 9.1 MBa63ba63012a30b55d90ac6115a6b1303c7b8eef7cdb5b8a66e967ff7ed12bf42
D1 icd_fast_nu_mpw4 7576×107760, 32328 7.6 MB1c5a6629334aae58e8029285a403fd17484cf02a9584c7efafdc8bb7ec7935bb
D2 rram_testchip 7576×107767576, 32328 9.1 MB46d1379e05c71cd0cd88bda00e87edfddad9d102f87f3eeb5d1d35f7d3e671e7
D3 rest 7576×1077615152, 32328 14.5 MB75fe82514712acbb73e31816076b5dfd24e25c33bb26bda7963a8f83d717669d
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 9.1 MB1d59eb0a3f6983e42391b6130b3a2e141a7a2a616606a25b05bfdfc623febe55
D5 sky130_radtol_test_chip 7576×1077630304, 32328 11.8 MB1441eb7b717e21352bc435fddd22e761e5295e9138709a24c6cd55af084d37df
D6 two_stage_cmos_opamp 7576×1077637880, 32328 7.4 MB92981968585753ae11a2ce63d6313364feb14db351432562ce149eb46a3241eb
D7 ks-guitar 7976×1077645456, 32328 17.1 MBd935a3f4445e8c36ae0b6c45b1394893761a0ebd71b8a051710f0fa2f14c5263
E1 ks-guitar-2s 7576×107760, 43104 20.3 MBec3c4d14b8eb20c3c7cff516d2737116910f6599dc68c51afb57beec88ee4eba
E2 yifive_a2 7576×107767576, 43104 16.2 MB81b20d923ba79d7faf4d7749c19206cbcc8f8ef01cc218bd8ca09b80c9bb1431
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 16.1 MB9ac3a38be40ea1e8860b5313658bd7a8d44a33a4a7bf010cb1f176fddb478214
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 7.8 MBc35d864ba4c49d10f637fd62ed7e58d6141ece9538bb488fdaa44778a25f8459
E5 junga_soc_mpw4 7576×1077630304, 43104 13.0 MB70481dd474ba47ca838369ff0b007f4544960f3f9e1d38dc09b410e6bc12ab44
E6 ibtida-ii 7576×1077637880, 43104 12.8 MBc8b0725c00701d9f2bc7318d1b2f2d4138e052f0ab6be55aed571217698b405b
E7 azadi_ii 7976×1077645456, 43104 15.2 MB286c234f3d1f6b18b97eddfcc3a5de4b2ff5e9b05f5de7f2497d61258a5a29f1
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 20.9 MBa2e15fd351699d7073bdaa159cae340d6fc96171b0424992e2c456315401cf3e
F2 current_starved_vco 7576×111767576, 53880 7.4 MB135f80eb7a72c1ed135f127b253e54032be531bf0bc8f2992b1cf2b4de294a37
F3 updown_counter__test_ 7576×1117615152, 53880 9.8 MB9abedf4a236f34e1d7438c8b86cd4e31740055897fd1c290f371a71223289dbc
F4 skullfet 7576×1117622728, 53880 7.6 MB42a7be2e5dd59b1858293e54e0dbe1d306d2879159c4af84a610fea4917a32b3
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 7.4 MBba3821d82580ea56730d03f84c74222f861b554dcb3d3f02c2f49d69e1696ffd
F6 kasirga_k0 7576×1117637880, 53880 11.2 MB925069953928ca9ee298f0c20ac9dc0b49329fdca3049a9fa5b83868d8fc4531
F7 iotestvehicle 7976×1117645456, 53880 7.6 MBa9e9bc9d53d9670807c7a43b7c3bbe405c87a0dd936a0e8675c1f3bdc8f5d8c4

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-004

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