mpw-003 / MM4 Metal 4

the MM4 shapes of all of mpw-003

40 of 40 dies rendered.

208,258,373 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 (351.3 MB in total, largest 11.3 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_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-003_MM4_reticle.png
the stitched reticle, full resolution
116.8 MB 21a155b5a6b9721ff4bde83517aa2c40471a3647a7d8dee2573f5508e57c0597642e979b 45c0a24f54145a577576578295a572ba90d5d283a1b6b50b3f3f27aa162ce61b
mpw-003_MM4_reticle_overview.png
the same image scaled to fit 4096 px
5.9 MB 8adfb098c36de15f97ecafde079da184caf81905da316ce527c1e0931cb3bd29b10cd121 67a1a739c98f9ab7bfa93821fa00cb34131b33d08920e19fdd00663fa8445795
mpw-003_MM4_tiles.json
where every tile belongs, and its checksum
13.5 kB 5cbe27d58acb4cafafa8617863d49941f3006464f02cb8369d89136821451e1be9594bdd 020b592523bffebfd3339bd08e3b58aeeb709499e1eeecbafd3404663106ac6a
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 10.4 MB4026b79516fcbed05cf51c7bd21599fa2652ef8015ea702364d9fa0c45322bb6
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 3.4 MB62a582fdcdd9c5c0de67953d191fe66ea23fc2c9cde3d08a8a9b7ac48dd52d33
A3 openram_test 7576×1077615152, 0 10.3 MB161ee3e75efd2d252389b1c463a8898cf6319e18788d85bb790009275bf4b90b
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 11.3 MBefad83fd232c2d01be30b1d0b276f73927385fb83748156c426a772783bf2218
A5 crypto_accelerator_v2 7576×1077630304, 0 10.0 MB676e963b3c713d9d8593cb8a64ed487e5c6ed3156c7b6d11e10185936bb9c800
A6 picorf0 7576×1077637880, 0 10.5 MB84bbeebeeb9d8879a6b0f2ea37fd60b6eb5665d6f07cf3fb95a7357573acd902
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 10.3 MB61ca6a32287b65619274208c58c3c472ef132fe6137c4d39c52342eaa5a392f3
B2 yonga-100m_ethernet 7576×107767576, 10776 10.2 MB2da7b111b21a8d0f8e0a5a351b8024e5c657f73805efc20180c92abaedde56ed
B3 approximate_multiplier 7576×1077615152, 10776 10.5 MB5339696a1785320db5099b46474293685eeea99604e0c42530109e9d3be690b5
B4 vsd 7576×1077622728, 10776 8.1 MB60ab17419c0ff411b79e212a55090672b09919ff8b569041ee731be6d499a0bf
B5 asic_key_value_store 7576×1077630304, 10776 10.4 MB4026b79516fcbed05cf51c7bd21599fa2652ef8015ea702364d9fa0c45322bb6
B6 mbist_controller 7576×1077637880, 10776 10.0 MB1ec6d40fad3c5cb3f8d5f48ef415e4efc31a04b675d148b720a2fcd26a4e4698
B7 riscduino 7976×1077645456, 10776 9.6 MB5d92afd489da7dee2dac490932c38d0d5b482ba7ee5ac840757cce50bdbc5418
C1 caravel_peripheral_extender 7576×107760, 21552 10.4 MBf940be3df1fb9134fc3c4dba2440ff987d11a64e91fea3fcdd2de0e33510f81f
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 9.9 MB1104655f23ff874f141f430ebcc55fbff54d67158d7f0a7373a587be129be984
C3 class-d_audio_amplifier 7576×1077615152, 21552 3.5 MBbea7581b5876e203f7d47ede43f448f288aea46c3e3ea6ad23dcb325667d6c28
C4 efabless_processor 7576×1077622728, 21552 10.4 MB4026b79516fcbed05cf51c7bd21599fa2652ef8015ea702364d9fa0c45322bb6
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 10.5 MB3c77e2f2310d424da931d78a86e7bc6ff8c2f7ea4d76cfb72e7ac6a080de50c0
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 3.3 MB583120e1e17307cf440d9b2b25b94db4771ef01a4105d107ccea54ce0b6c0dc4
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 3.3 MB01c18cabe803566ca31dbf657ae00b7dbe13334efccb24bb7ea715e16fe0034a
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 3.3 MBed574eb57099291a9c284cf7c249ad55bd2ec361b87b03c1e48ac971ef7ad287
D3 sziklai_pair_amplifier 7576×1077615152, 32328 3.3 MB18673ee215cc1d37788304d9d4c02ef82ba419b332562a42aefb3cb97c1cbb12
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 3.3 MBbd5e00b472139ee9bbb209b6dfc5d587d72f4bd2d8cedeb0ecae4b8b341b3258
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 9.9 MBb95eb827939886f6237e6420177be043aab487bbeebf91d5989b6410f13ef729
D6 rotfpga 7576×1077637880, 32328 10.6 MB62ede3db012bf7c6899cac0ee25376b39201b1b2d870f26ce2178279ddafee50
D7 treepram 7976×1077645456, 32328 9.9 MB9e2779eb1dd9c8286a1ab43f5234c0aeadda2d51e85ae148df8750cd9d08d385
E1 treepram-red 7576×107760, 43104 8.9 MB434ebc3b35d62b1edcce542aface7afe509d3e9f3c5fe5bc65cd72f770c65735
E2 caravel_jacaranda-8 7576×107767576, 43104 10.4 MBc70115d7e67133baaf9e876ed251745975e3971c3a4585ce042ce71f0e66db83
E3 sudoku_accelerator 7576×1077615152, 43104 10.3 MBaa43ea80c38ab59248f50c9e9f8ff9b0a4288e48f8733b05d10da4946a96d834
E4 fixed2float_converter 7576×1077622728, 43104 10.5 MBbf2d75e9c5db4b410075467aec8d9a638d23fd8e0d105bbbef380869f7289f77
E5 high_speed_adder 7576×1077630304, 43104 10.4 MBaabf6f1c65b1d282b0f99609210b2575f34da0be1268fe63681e37823f6240a4
E6 my_proj 7576×1077637880, 43104 10.5 MBa8925050bdfc44ba9a3b044638a25d1c9e0934564ba113b62f26b200288b1095
E7 pwm_test 7976×1077645456, 43104 10.5 MBf2579a47ed21b9391400c5e8033b6ae4cda175fc658992649e67fff12a45e8cd
F1 elpis-light-mpw3 7576×111760, 53880 9.4 MB904e40883a1bfcbb97c7e322150d83b3943303bddb03d4efe40554b19dc91b5e
F2 vsdbabysoc 7576×111767576, 53880 9.4 MB5332c9856913ffda40802f8be0636ec2bac9f13bf819d2f9bdda28b0a5affd3d
F3 vsdmemsoc 7576×1117615152, 53880 9.8 MBc0af1c2c2ca0fab45bb1b04afb2870c8776b50fe82ac91efe627b24b6f7e27bd
F4 caravel_sram_test 7576×1117622728, 53880 10.3 MB75b14de4c674d4eb2d3cff42056b208f7df1d3e86be905611d58c3e44c276245
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 3.3 MB4d5a635f7e21f5e5ad3871b2067a2ca29d948b364300230556bab60e73793db4
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 10.3 MB72dca3c0ac7874e2745c45f14ec38a4dd2225bd92bd79904d2a75ac19128d390
F7 caravel 7976×1117645456, 53880 10.5 MB71b9491939b3fae6b3f51f6e8dd6255dc0a2a32ef9507bcb6f7e9381569d3f42

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-003

Resolved: reticle 5CS8008AC, run mpw-003, 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-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.