mpw-003 / PSDM P+ Implant

the PSDM shapes of all of mpw-003

40 of 40 dies rendered.

26,562,100 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 (64.4 MB in total, largest 4.3 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_PSDM_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_PSDM_reticle.png
the stitched reticle, full resolution
38.8 MB 1a418210eabf76e77ca570a1f1bb1f98186214ffdd8644d33009e0217b0b4083d8edc374 ed12668766b8ab2e436a05ddb97ceb04a63899d88a6c9615c15c4590743e86fb
mpw-003_PSDM_reticle_overview.png
the same image scaled to fit 4096 px
1.9 MB dba496fda9aa30f7244505a24aac5caef1c8d6893d7626879e5e5a863d3fc096e8c76a04 45ffd6842950cb29e43721976aa902ce61836af87732e8ba981ce09d6e516e01
mpw-003_PSDM_tiles.json
where every tile belongs, and its checksum
13.5 kB 793063d676ba58f7580cc3cac0fd8c28c35c22cc55722ae1163eee9dfe489098d5050ef1 3af3366d3cf7cd01f18c0957d49cd2ec40add9242d586a0cb918f58a120e0edd
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 1.3 MB114974608c71a9d57acc15238472e7c1cb834c339ed4c116bd3097a0fafeb806
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 1.1 MB88e198e492d9739aefb9318c233f96e8f0046288a906a98c80811c3a2085af54
A3 openram_test 7576×1077615152, 0 1.3 MBe107464516e5e988a993006e06f54c168256dee3299a326a62fac1aac92d6697
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 1.5 MBd5b0a8e0c7767c4f7764c04b3594d3df8f1baaf88d8c411436fc2fb077fdcc41
A5 crypto_accelerator_v2 7576×1077630304, 0 2.1 MBe7ef16c432b81badec706c8573d0678cdb84e55660f0a81119a65119ff22f25c
A6 picorf0 7576×1077637880, 0 1.5 MB85355b0c87580170e045a8f3a0880e0147f5b8b308a40be0aeaf1fefc0bfe59e
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 1.4 MBd777d46730768698b43d00fa34696da632e2c5eafeee498907be717510e4dd13
B2 yonga-100m_ethernet 7576×107767576, 10776 1.6 MB96ad91f3a00540f0989a674d1dee6821fd1d07e63de0f47608c13e5c8e17edc9
B3 approximate_multiplier 7576×1077615152, 10776 1.3 MB588feabdea79c0fe7e2825908b342702910dc4bb70930a7aff534239f551ed0a
B4 vsd 7576×1077622728, 10776 1.2 MBcab7e60e57e89873a6cd8c361335dcea0a2a6023e1a174a1374ca765b78f3cca
B5 asic_key_value_store 7576×1077630304, 10776 1.3 MB114974608c71a9d57acc15238472e7c1cb834c339ed4c116bd3097a0fafeb806
B6 mbist_controller 7576×1077637880, 10776 1.9 MB047b2ae385e6ab3233cb697f8f155c592417c0214d11867cf6cffcbd822bd3cf
B7 riscduino 7976×1077645456, 10776 2.3 MB8849e22e11248630f070ecea1059c19900b72b8aaa1ab569d7dd64c0d40777a4
C1 caravel_peripheral_extender 7576×107760, 21552 1.7 MB4caf0f3953fdb58ee84e21b2c45c46e8430d07b2632bd1d48be27942e093e1ca
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 2.1 MB219eb7bea8e276d434cc0749f7a904c5118c1e4bacc91ad64279db41a6d61b4e
C3 class-d_audio_amplifier 7576×1077615152, 21552 1.2 MBa7dcc7b647def28fe2b867cb9809d82202e4857bb0f43dd7151a27a5e23b0621
C4 efabless_processor 7576×1077622728, 21552 1.3 MB3a132dfd8ffe3261ce009e8262e029b548a60888abd2ef246f57ad359ddbc761
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 1.3 MB6f1ff15da81404765c44c54bd3edec6d120de08c215517e7515107efd5a8b09d
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 1.2 MB3c07ef42108fd730938cbb6b5e2123888d41a8fe3aa24545f4678a2c705f9ca6
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 1.1 MB85a032de51966dc34f21dac8dd247cc462c2bd718d1e8a531535113bc9585106
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 1.1 MB15baf4333268e9654ccc0fa892a4626c99c340050ec481e7930471d2520070cd
D3 sziklai_pair_amplifier 7576×1077615152, 32328 1.1 MB00e36464295d41cba2fd475c1729224e2513e5c49492146a4866aee9f74402a2
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 1.1 MBd8f291342f75e179a0a23da88d68e3072fdeec71578d2a558140db200c910406
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 1.8 MBc9cd25c0fb4916c5fb03ee00605c5e0a63f155c8b8fe6d04858ff9dffb8e791c
D6 rotfpga 7576×1077637880, 32328 1.6 MB3b9d0e450a7cd6e96b97330211d915bac5a4c09d2d930acfa59390e205baaca8
D7 treepram 7976×1077645456, 32328 3.6 MBaec1dd699a9d30d4b74990d6bc68054b6b727a22fb1affb5a2db82829574cdfa
E1 treepram-red 7576×107760, 43104 4.3 MBfbba87b9d0906b3212629efc8e2b3cd3c6b410006acab1c14f11ec84084ddeb6
E2 caravel_jacaranda-8 7576×107767576, 43104 1.6 MB0154df3674d2131f9c633df59ea03ae6a19c8e265097f43476ac40a7af7a826f
E3 sudoku_accelerator 7576×1077615152, 43104 1.7 MB8dced3e708e85f4bc64f56b51c81e1fa3d99f3f4ddf2761176b9edc461d69c17
E4 fixed2float_converter 7576×1077622728, 43104 1.3 MB540d77b3eb97aa74c686602753c9ce70764455d46f3ef9d92fe0b3e21144451c
E5 high_speed_adder 7576×1077630304, 43104 1.2 MBc787c925042d2ccc20b59df8f789b25da908a1c3191b7e47aa955b40d3a5bd5a
E6 my_proj 7576×1077637880, 43104 1.3 MB0c287c3b10c497962f18eda168cb02a171b2f654222d80dbd74677d22dfa158e
E7 pwm_test 7976×1077645456, 43104 1.3 MBde8ab983f35ab0ec4a17960a8a342db56d64a00ba12cb1ff76f049457fa650a4
F1 elpis-light-mpw3 7576×111760, 53880 3.3 MB1c3ef1b791e04f1c14ad073f3c1acdfb8d4ee6ef80d61bd4e8e6fdae725e05e7
F2 vsdbabysoc 7576×111767576, 53880 1.6 MB7c2b23581fbac5cd6aa8364e608904348a508827459ef188a4a02dbfb9e9cbf8
F3 vsdmemsoc 7576×1117615152, 53880 1.8 MBa9152fb860bd7b7a9dc7b59d94c96cabd29fd19e9985ba7d6ea3e3f809749a02
F4 caravel_sram_test 7576×1117622728, 53880 1.2 MB2344e28a403356b65bd53ee35a9ac7c9ee789f64f42a54e65bb4dab772a6174a
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 1.2 MB208992ddf891395d1ab68f50460085df2db7379ebf148f92eb640cf382eae438
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 1.3 MBa757dc655fbd6a79828ae2c053cd481c4ac44681d1cbaabd2cd098593a3ba6ce
F7 caravel 7976×1117645456, 53880 1.3 MBe2a2b00994d63ecb8a2aaf7c92c4b47a6468849ab321110f9c955c1e2c8d37b6

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 PSDM on mpw-003

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

Mask layer
PSDM — P+ Implant
Process step
81 — P+ source drain implant mask
Drawn layer
94:20
Layer on the mask-layer GDS
32:0
Detail
PSDM = psdm OR grown psdm over pnp emitters
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.