mpw-003 / LI1M Local Intrcnct 1

the LI1M shapes of all of mpw-003

40 of 40 dies rendered.

185,820,719 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 (232.6 MB in total, largest 14.4 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-003_LI1M_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_LI1M_reticle.png
the stitched reticle, full resolution
122.9 MB 98eefd6808e130a38aae6caf510a1993cfcbe712fedb30fdf95c486391734b64f7a182d1 b2943929e84b8ea1e12091498f5b0ce7ea585f0a884b6e8cf98044276ccd326d
mpw-003_LI1M_reticle_overview.png
the same image scaled to fit 4096 px
4.5 MB a912a3c9371cb1c1e2c7db25a353f259a9ef204d5b1fb125cca661076f9b1cef01820154 1b8ae152da5967c0752fbc58b42341b61652fd6f2893b5b6599ff4533fcc5b20
mpw-003_LI1M_tiles.json
where every tile belongs, and its checksum
13.5 kB f999be7b1b341356a000a5b76c7c29a5bb7508c4996b18ecc2080a54d47bff6cd6320bff 9c4181a4012a40ecf12cef9f5314e4ae53196bdcd66692f4815520f4a3e344cf
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 4.7 MBb3ed353ad9be453931efae688936fabab2221d681907a85277937eb8e7b0db29
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 4.4 MBfe36b5ea3c934d72a7c5ca717ac16cf08e05eac6144dd569ba408664a3049637
A3 openram_test 7576×1077615152, 0 4.7 MB3906854c1149f5669b1e71bbe0f63708099197e824f2d68c65faadb51d4ee66f
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 5.7 MB18bf4e917f0913b85693e113c2d22d14f1d520a7ca7bbfb6d481032c5c1bfc19
A5 crypto_accelerator_v2 7576×1077630304, 0 7.3 MBa91060548c96fb9fad4e867b9ad0029e8f93a2c097c40b5c5e5da3085b241821
A6 picorf0 7576×1077637880, 0 5.6 MB198fe6ff44d08a3d9eaad8306f223ee92207d2cd943027ab4629be774842b1f6
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 4.9 MB3d5de01ee161e98fe89f5dccef64ced44969cc1bff0d354a843832eddfdca787
B2 yonga-100m_ethernet 7576×107767576, 10776 5.8 MB24676819b043b1d382098ab6453fd56badf0cebff1d24ba9b6ceb43f1d310250
B3 approximate_multiplier 7576×1077615152, 10776 4.6 MB1f453290789baa343749f89109118c7806009952b277a557caeda3476e759fc6
B4 vsd 7576×1077622728, 10776 4.5 MB424b55e28ea71ac7156534d1a8aebcd82ac816b6c946f94004e4761357e66f7c
B5 asic_key_value_store 7576×1077630304, 10776 4.7 MBb3ed353ad9be453931efae688936fabab2221d681907a85277937eb8e7b0db29
B6 mbist_controller 7576×1077637880, 10776 6.8 MB77fa3cf520b9e653b7b84fa6baa9dc943510e6c3f55d62b8a9c0930cccbe5431
B7 riscduino 7976×1077645456, 10776 8.6 MBdded1b409eef05213b9b8b03b67d9dd717f6092cdf74ea21bbcfbc668ee700dc
C1 caravel_peripheral_extender 7576×107760, 21552 5.8 MBdaf6ad4005129ea067fedc64db252f3ae09959a95b6866439c157376f54f2b26
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 7.4 MBc77389d69e1c475ee1ad38ba65396296385e1ffce60658db06a14b73030f3fa9
C3 class-d_audio_amplifier 7576×1077615152, 21552 4.5 MBb28ece0e2df6ce828895b8170e6d09ae216d10589ca25174b1ad8ca949978841
C4 efabless_processor 7576×1077622728, 21552 4.7 MB8a8639ebe086fe2a92f88acaebd90f13718393829d23024c48137b8d3bad365c
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 4.6 MBb87c604c72499faeabd520e29f763699d688c9dde2cc627a231d000d198424a6
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 4.4 MB32825d0afa255180d42408b7bccef0f24dcb2992ec6cec2fe5c6819ffbbdbd35
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 4.3 MB100fb11a768c335113b539becbaa55181a832d01565eb0b64e467d3cbb9c114c
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 4.4 MBdc073b1e47ddc8e9b98a15b9e634516ec8f2eeda9fe6657fbe310a8e96701dd7
D3 sziklai_pair_amplifier 7576×1077615152, 32328 4.3 MB554985a00c14a122966ce208ac7282d278eb32cfe420330a2e2cac022ba8600f
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 4.3 MB43c99333d2e230d1efeac155d1f94db685b74e291423de3f0621bf2ac2ba2ede
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 6.6 MB0a24b352e49cdb3804bf86320d60893c213b0954038a048463638b15feb7cc39
D6 rotfpga 7576×1077637880, 32328 5.6 MB4c516bdaba99c08c4db0f52fd394f592a689f3b5546a5b03e7b6cf654709b967
D7 treepram 7976×1077645456, 32328 11.6 MB93e1f2920253c401f9430e48dcd8f4482ad4ed35cd8c1108909a357ef90dca71
E1 treepram-red 7576×107760, 43104 14.4 MB42efe60a84577a902e8546e0d54679823768c7197829f5492d6cd7eb69246218
E2 caravel_jacaranda-8 7576×107767576, 43104 5.7 MBd245973191cd5e073b810f7b6022c1a6741804863b51ba3a5c612496b5b80517
E3 sudoku_accelerator 7576×1077615152, 43104 5.9 MB56b23d4181d1e5f2787a51d78e6f27e7272388ad5fd44e06a13f90d83a5490ab
E4 fixed2float_converter 7576×1077622728, 43104 4.6 MB6664a166d4714c12ad78760e93e3fbc43522acaf179bbd44823b27d5bfa92026
E5 high_speed_adder 7576×1077630304, 43104 4.5 MB4195a43c7638c48fa28bc8c87801807a2442812cb432d8f1c68b29a05e188706
E6 my_proj 7576×1077637880, 43104 4.7 MB6d2a62e6df235603835575779d988c9d5f95798ebcd0f8f2e9f2ed5e23f8f058
E7 pwm_test 7976×1077645456, 43104 4.7 MBb99a42e3d5113b41266543e36dd9a8afb1ca36f65643f55d2252ac351321bbbe
F1 elpis-light-mpw3 7576×111760, 53880 12.0 MB54d86c9768987908a79924930f6a2c9cff758b9e917e7bb59783828dd9e709d3
F2 vsdbabysoc 7576×111767576, 53880 6.0 MB300a00386b2e74e0a771b819ba4bded1fc2be68ed736c0152ffd0e4360f54700
F3 vsdmemsoc 7576×1117615152, 53880 6.5 MBdc55d34a56f42d6e44e2056cff7ec9d8de898991fdd8e352b18c15bc939768cf
F4 caravel_sram_test 7576×1117622728, 53880 4.6 MB370ad118d07346fcd25adcedc3690158c81733da44c56bb141b6ba86a8e6b58a
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 4.4 MB3abdf4a37a81ee7bf4c397379a98522d0bb7d2dbec53365079af15c8e1214c60
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 4.7 MBd89a0a5f8e34cce53639e9dca34e3b1a115779dc860bb828ee437fcba1ae3b01
F7 caravel 7976×1117645456, 53880 4.7 MB7ddb125fb6ff97e4ca38b3e2b48615b5cd630e403df40f9141fa084da520ad8a

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 LI1M on mpw-003

Resolved: reticle 5CS8008AC, run mpw-003, mask LI1M

Mask layer
LI1M — Local Intrcnct 1
Process step
102 — Local interconnect 1 mask
Drawn layer
67:20
Layer on the mask-layer GDS
56:0
Fill layer
56:28
Also
LI (Metal 0)
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.