mpw-008 / P1M Poly 1

the P1M shapes of all of mpw-008

40 of 40 dies rendered.

222,110,983 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 (345.1 MB in total, largest 16.2 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-008_P1M_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-008_P1M_reticle.png
the stitched reticle, full resolution
196.6 MB f35439257cc11704be19810cb350165736f72a802e8eaece0a64e93b0238f42602cbe993 7f07977d49d635fc985f459f34f77c59f2ec3451acefe370a08dcb6aced0776a
mpw-008_P1M_reticle_overview.png
the same image scaled to fit 4096 px
7.8 MB ef4ed0233dac7c91d47f65adb956fa14b97be51960c75edb0c00bd4c34c2e5e790eeb33d 034ca455d34e6f60184ba279e32471acd3d7ec98e0ec9f416a333113b722203a
mpw-008_P1M_tiles.json
where every tile belongs, and its checksum
13.5 kB 01202e0ca0156eaf97d50c0437b0a274dad4522cd21df8c4b45d74d6c7f19736445c3903 15187bd273e204fceb531ae3902315962ad6dd41d6c5aabf2a553663df8400ef
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 wishbone_pio 7576×107760, 0 8.7 MB8b365ed50d19720377c9df42fd004fde2875e7b2a135aa858295cd29e45714b9
A2 iit_indore_mm 7576×107767576, 0 7.2 MBcc1f05f13e7e9f9b633e6dbf0a8b205fd9f08139535219a300ac9e8b144612f4
A3 energy_efficient_sum-of-products_circuit 7576×1077615152, 0 7.2 MB9903d6bd27e96058ff291334a7f38303f0ff1b87eb31b2d1ec452adaab9a1cd9
A4 riscduino-dcore_d4_ 7576×1077622728, 0 13.2 MB6cf3813f1c5702116ca012faaab217bbbda765d502e117d9aeeafafa3de0fa33
A5 riscduino-qcore_q3_ 7576×1077630304, 0 13.7 MB93a6957ea5f3c116b652cb38e2d384823ef5807b48c62dbc2541193ad658fe07
A6 caravel_mpw8 7576×1077637880, 0 7.3 MB3e2cca4dd11b0179276cff402ca3abb6d3ebb8292ef4f509c4666d276ba2f1fd
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 nanofabrication_project_using_openfasoc_mpw8 7576×107760, 10776 7.4 MB23581ef07f70b7efa2fbefe7e08db6d13cff67c5f913c29c024a481e3d42057a
B2 sramtestvehicleg4 7576×107767576, 10776 7.2 MBc879ac5bfa8863f2f12a03a76881b0aa2737429a1c225b4fcb2d0af0fed34d23
B3 reram_crossbar_rerun 7576×1077615152, 10776 7.5 MB9b620bd13117d7d5dfe4e1fabb7589a2b24855dc54ea6262bff4fc412c58aa9b
B4 tinytapeout_skullart 7576×1077622728, 10776 9.8 MBf6cac90a58009b12f665934f2f85e960943712433ed0c7b2114f4d0ce69d0ccf
B5 soomrv__mpw-8_ 7576×1077630304, 10776 16.2 MB430c66f7261ef30f549c37d9a97ecf0cbe03ebca351ecd2b438088cc56aff19f
B6 clock_divide_selector 7576×1077637880, 10776 7.0 MB0e21cf989f450a09a25d953e662621e1bfb4ff1bca3a34dcaf130ad522333cbb
B7 reram_module_mpw8 7976×1077645456, 10776 7.0 MBdddcd9c7f96c7b52c036045671d746bb73242155bcb3c433c59a7b9e43e80998
C1 shapingthewaves_8 7576×107760, 21552 10.8 MB80fc2cafe1c3716556b49f3e83593a52f590fa53f3472909f075f58f29997e7a
C2 leosoc 7576×107767576, 21552 8.8 MB98eae9dd71cb65a5aaab807bce4edf377e5a544aef895fdd0601f158943ab711
C3 decrypt_aes128 7576×1077615152, 21552 9.5 MB73174e15b411a6d5f04ceaf7379f68fb34e571489fc3e5e7aa312288beba4f46
C4 approximate_adder_axha 7576×1077622728, 21552 7.2 MB5927cbe9d369c5c8309f96e5655340dc6f45f9547a30398ea57bf9aaf2ef975c
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 riscduino-pxt1 7576×1077637880, 21552 9.5 MBc6c4f410994ecdae14c4fcbd74d9d6e7a63704cab456bb5bbb1c7ce7cc52ac6b
C7 fitbit_project_using_openfasoc 7976×1077645456, 21552 7.1 MB3cede54f162870e4adbf1027a618b41be9d60d9b96074537d93f045e7f252e7b
D1 rift2go_2320_sky130_mpw8 7576×107760, 32328 15.9 MB131b341b811529f714110745ac638db5702218077df5dea0a60b1e5c79401b5f
D2 hyperram_controller_for_sky130 7576×107767576, 32328 7.2 MBb38098f4971b6853f2af5e32fe2c639030cd8dbce5c199c7d5b71f7f45dac392
D3 hardened_alu 7576×1077615152, 32328 7.5 MB4a1146a8467331471a0d1671ce41c693869a61cd4045e8a565a2046823f18ba8
D4 an_open_source_hitachi_sh2_for_motor_control_apps 7576×1077622728, 32328 9.9 MB34c5b5db58f3753f787815f341654f640d8693b389e31926e838ebcb91507ee0
D5 mixed_signal_circuits_mpw8_dec14 7576×1077630304, 32328 6.9 MB7a44963e96f6e64bc0bdd78d6f9d713a4b2e808286daa9002deae7eb4b3a26c6
D6 gf180_vs_sky130 7576×1077637880, 32328 9.1 MB702c90baf2680b8382247500bc1ff4a089427e18ca36677b2a6dc54343ed8eca
D7 iiitb_tlc_mpw8 7976×1077645456, 32328 7.2 MBffdd40cc8284456d9a423b5c996af6aba10a97ab9c42a12c88db7c53304d8304
E1 iiitb_sd_mpw8 7576×107760, 43104 7.2 MBfa658ed605808f75044796c04e00b15f3b5b035098a8d0a124fd0edbff8e3953
E2 iiitb_sfifo 7576×107767576, 43104 7.2 MBcdd2455d2f3c6a10c03b19ee51ed2336078dc66d2ae064d0b19f0c81ab0e09bb
E3 iiitb_alu 7576×1077615152, 43104 7.2 MBcae2679cc126e47f59440a8d7a7cf95c60556b40034675874a57f7b198eeee46
E4 ppcpu2 7576×1077622728, 43104 12.9 MB751af1a5bafebf5a8c49491251286b7e1b15a87d19f8bfefda024f266dfc287b
E5 mega4_reram 7576×1077630304, 43104 6.7 MB6ba46b86b4a19f13918cad611c8fe88b0517a1fa72c76b2178d7333f3ea1533b
E6 tiny_user_project_vgaclock_mpw8 7576×1077637880, 43104 7.1 MB9c9f6f9d44398c82cc40811a59692726446e7358b3d56d12e0d244452a82376f
E7 sky130cla 7976×1077645456, 43104 7.2 MB64f0aa9794a52afd0311ca807f0ead1f4c6d4a11206d591a4315c4d4e9c29a86
F1 uetrv_esoc_v2 7576×111760, 53880 8.6 MB02a83cdaf33e515dc67b14959d0ef66d08d93535d9dfc04f6ddca236b12d5dee
F2 sequencedetection1010 7576×111767576, 53880 7.2 MB90fc4bcff5571e82315e251ceef5be0c3e1a74a7a84076f45fab321e0ebbbfa3
F3 testasynctrimux-mpw8 7576×1117615152, 53880 7.0 MBaeb07b0993bdc2b9b2b161c22217086a492df3ef7632d12c4522d2c39783f282
F4 iit_indore_dadda_multiplier_mpw8 7576×1117622728, 53880 7.1 MB42d750ba5332f3b496b74c3f1e81bfc7ec44305ab3f5c993a04e38d58339d75e
F5 modified_baugh_wooley_multiplier 7576×1117630304, 53880 7.2 MB231ac3228d16ab6b0fec4005dc616015ca262ce8be43acc5972aaaeee67058ea
F6 arbiter_puf 7576×1117637880, 53880 7.1 MB74fd489a16f27ecbd72bd201eb30e3c8f12e2b1755111b09f5e487d99d355c9a
F7 unigate-sky 7976×1117645456, 53880 9.2 MB5c4455f251d149f5c08efedf7b791d8cb3fc91987d392f75c1235063ef8c7f54

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 P1M on mpw-008

Resolved: reticle 5CS8017AC, run mpw-008, mask P1M

Mask layer
P1M — Poly 1
Process step
61 — Poly mask
Drawn layer
66:20
Layer on the mask-layer GDS
28:0
Fill layer
28:28
Used in SKY130
yes

mpw-008 — SKY130 MPW-8

Reticle set
5CS8017AC
Run date
2022-11-19
Submissions closed
2022-12-31
Projects
144
Identification
inferred — Sequence after 8016=MPW-7 (8018 is the re-made MPW-4 set); packing list 2026-08-25
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-8 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-008/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.