mpw-003 / MM5 Metal 5

the MM5 shapes of all of mpw-003

40 of 40 dies rendered.

9,322,002 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 (13.6 MB in total, largest 378.2 kB), 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_MM5_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_MM5_reticle.png
the stitched reticle, full resolution
8.1 MB d36f5fe3912ae7b314dc5fdf2414a057f92fe695f01764fa46e99a8520afa87ef015a826 99babc97b7e65110a009f9675fefc808b7e96e939031457c05e2d7ed4d156641
mpw-003_MM5_reticle_overview.png
the same image scaled to fit 4096 px
3.9 MB 5e10d621c819e43284a9faccd9c84d8c8b38c128527f3e6ca208a696f2b7322cceeab47a 885c641b8b3e52f1b80b9a7074347aa095e9759ba4a089289b455b6e39f8558b
mpw-003_MM5_tiles.json
where every tile belongs, and its checksum
13.4 kB 88f6f70361af613696ee54efb42093221c96b84b3bd6a5b9c11c2bda1edb75c6653873f3 8337f96ca5648a47f562a70e3466d85e4854da22d6f48895052555e251162f3b
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, 0 327.8 kBdaf72f41947c9a62da0ee5e79dfcb2406aa744c078ce8fa5ec5c664b89aeb2d8
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 358.1 kB57a6cca11b718e864525e98c286b010ad6bf3692a8c1c59e333fc9495ba80606
A3 openram_test 7576×1077615152, 0 327.9 kB80bb1b52e8093625565832724fd659c4e0ab46879f0961de537ca10aa3dea4a7
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 327.9 kB93e209fd2b22968ca1de653d7be71aa0e4658e8a31d3b01df0f7f1e3d84f86d7
A5 crypto_accelerator_v2 7576×1077630304, 0 327.9 kB2b5ecbe6cba9814b6de0e48e609bdc2f4e8e85d870d3fd70086f49c73bcd0722
A6 picorf0 7576×1077637880, 0 327.9 kB404d8f7f3b939a308331d516a98944f586bda723350755da18f2625d666a1738
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 327.8 kB6f8062f0da002583a8c5c0a08759478fb16e4ce12ac948f245c40799953faf07
B2 yonga-100m_ethernet 7576×107767576, 10776 327.9 kBec06f664aa736b999e0b66398c57b494c57bf21892a8d8bd079c9b9589eb8409
B3 approximate_multiplier 7576×1077615152, 10776 327.9 kB721fbe9b19e450676658e84af77fc6a50f0bf8ae47c3158a11ddc6b78a71c891
B4 vsd 7576×1077622728, 10776 336.0 kB50c279f55d238d1c38582264d3ff1afe0a2d717dbe1691a51635dbafaff33d23
B5 asic_key_value_store 7576×1077630304, 10776 327.9 kB4afec0340aea42a874c15fb9546c23deebf98ae9bb12153965abd8da43dacb83
B6 mbist_controller 7576×1077637880, 10776 328.0 kB38968a95503262c3ad1d74306a8dae19d0fa31bddf8b68bd38ff20ce434513e5
B7 riscduino 7976×1077645456, 10776 312.4 kBff5146702c93b0d38ae63a10ca11f0c664d3dda4d8b905c880a995fdd706efcf
C1 caravel_peripheral_extender 7576×107760, 21552 327.9 kB36d2943186149373d8b7c94851cc1f6f6d3f7a042b2906aa8cb725f9ed9fa0e7
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 328.2 kB8192a039a65ffd9c1bcfdaea59562f877840a033ee17885c31ca33599e824c61
C3 class-d_audio_amplifier 7576×1077615152, 21552 364.1 kB8664ca157fc981470e5edfb42877d582c599ff1012dd0291620e71cbbea60a76
C4 efabless_processor 7576×1077622728, 21552 327.7 kBaf8f11cd0c6f8f667b847c9053b47660dc724823ca00f1b70d4a0062aee8ceb6
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 327.8 kBa4403696e9863982b435eb51a6e8fded176d205e4c60e938fd3d0d0d546badbd
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 356.3 kBffc808bd7dbb25af8ee052459e4b7a82d9a591fdbcec0ae5f891aa8dd2ecf8f7
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 351.9 kB1b71b96604e52d18ac9e1e76d0e1da4257876384e81e60233920d19f15c348d5
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 351.7 kBf618571cc1a5f3184d033d4c6b5931d97b932c1cda3f83de5baa99750494f69e
D3 sziklai_pair_amplifier 7576×1077615152, 32328 361.2 kB9fce48b25b517a0b9d58143ac583be4650ed4be06e830bb5463164abd52bca09
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 360.9 kBcdbd4c9ff60f3a53ec98af6b155aa2cf7c3428ab8510867ca1fbd14f298cd965
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 327.8 kB88fd2463b6745e8333dd722075ff47bcbd6b97ac00d8176a8628638ad14db4b3
D6 rotfpga 7576×1077637880, 32328 327.9 kB540ec854a05c8e5bc524bd6016c8e904b1954b6ede521f99e3ca8099599c3dd3
D7 treepram 7976×1077645456, 32328 331.8 kBb6588e0792604821360fb88cc758e080e2fe3fc91755e02b797b65b36ac79194
E1 treepram-red 7576×107760, 43104 327.9 kBf9ed44ee013292618fa26e43c0d3d5e18faa60d556f76d52249ed0ec51cdfce3
E2 caravel_jacaranda-8 7576×107767576, 43104 327.9 kB15648d5c9f2d4f4e64ad2d0d6be37fd98051acce24c3c9c08618c4e4114a2737
E3 sudoku_accelerator 7576×1077615152, 43104 327.8 kBd932f697b44034462713c94d2c13e4bcea7e6634a012647f457fdcbf4fec364a
E4 fixed2float_converter 7576×1077622728, 43104 327.9 kBe316c0171b1c0762e7a6ef0c3bde15329b4e2dd13d29324740a3fa53858a8cb6
E5 high_speed_adder 7576×1077630304, 43104 327.9 kBa9e1f078e6db4d7475a8dd3f06f7ab1478dccae7bffbcd03f57dd6846c98f328
E6 my_proj 7576×1077637880, 43104 327.9 kBad876a50b4d63ee0d63ddb66eee937132b65007ce3f768548c3b4633539c10f8
E7 pwm_test 7976×1077645456, 43104 331.7 kBd3600dec70c60b060093634c26335183c7f81688f0a6b27ed3c403628047e2e0
F1 elpis-light-mpw3 7576×111760, 53880 331.8 kBcc5555e3b8293a533ca9ee255cbc41b2d2af7faba5fb985efbb0161e4dea3bd6
F2 vsdbabysoc 7576×111767576, 53880 331.8 kB5a941ef6420959a0ce098b4feb611d1ce986b9b0ea8ea0211351a3e069957298
F3 vsdmemsoc 7576×1117615152, 53880 331.8 kB8800a7006fde958fd49df324e809f05f769994fb46683cf2a0a4891ec2de360c
F4 caravel_sram_test 7576×1117622728, 53880 331.9 kBe356b6c5a04f2391d19599bab12e2df5103660ee6940f917c61067504fa46f63
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 378.2 kBb0c94566db95a13ef3ee6830ec2e13aa58494e409acfeda3904582a98118cf7e
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 331.8 kBb463bf95e8a2f842d52f511e3c487dcd4653124cb0fd7f7a9652be5607392a42
F7 caravel 7976×1117645456, 53880 336.0 kB9cd3c4169b0ef3689a318ed73e442ee6f22649deff817b78f004c145752dbc44

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 MM5 on mpw-003

Resolved: reticle 5CS8008AC, run mpw-003, mask MM5

Mask layer
MM5 — Metal 5
Process step
162 — Metal5 mask
Drawn layer
72:20
Layer on the mask-layer GDS
59:0
Fill layer
59:28
Also
Metal 5
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.