mpw-008 / NPCM Nitride Poly Cut

the NPCM shapes of all of mpw-008

40 of 40 dies rendered.

30,731,266 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 (92.9 MB in total, largest 5.9 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_NPCM_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_NPCM_reticle.png
the stitched reticle, full resolution
70.5 MB 1d1ac74c5ddee617e6b979c8f902eae224a54fa4af0e9006f6d398c8be65a8736d3d74d0 393909a183cf723f612d935df91eedb793b26ac28e5535b93d3eefb1804c33ee
mpw-008_NPCM_reticle_overview.png
the same image scaled to fit 4096 px
2.3 MB 96fbcac9932dedaaf2b0204bf6355b6e36b185ce12a9f40d97d685b93c91b437be496dfc 1eb49e19415b7caf970418edfa72d60e4711f97bbc83807fe2ed339b74edae86
mpw-008_NPCM_tiles.json
where every tile belongs, and its checksum
13.5 kB d00b99b0635451195b0b0bf40db35f4e360bad566841e435d56838428e0a09c3882d5470 6f772265b46936c849ddbad870c781fe5a78ae041ef641760a0f0ffa2da85f35
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 2.3 MBdd530b4d42220a125656b1f99e3cb1fc7fb0bd6651e7c3bbfb1a3c1b56c9c7e9
A2 iit_indore_mm 7576×107767576, 0 1.7 MB75aa35a5e077ffb92fd52c5a8aadcdf3b7abb74d7e22dfc46a9818961ea1a16b
A3 energy_efficient_sum-of-products_circuit 7576×1077615152, 0 1.6 MB7f6f06867df074d93388485dbdae8496a4ab6b32875bf368f9c7d1e2dd50d70e
A4 riscduino-dcore_d4_ 7576×1077622728, 0 4.6 MB2c567b766e2f5783066a923bb1e5a1a8a7fbc8e1b1da515c9aadc7a32ca73773
A5 riscduino-qcore_q3_ 7576×1077630304, 0 4.7 MB868881cbb85e5a7c9b29e55acec8cce2fdc100cbc84c9ef4c390af7cc8d907c1
A6 caravel_mpw8 7576×1077637880, 0 1.7 MBbf53b3bf0fa51e60edaf4c49b9b75361359d8116e8edd5584068d7433e4f320e
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 nanofabrication_project_using_openfasoc_mpw8 7576×107760, 10776 1.6 MBbaeaff5693d9f50d5974f84908420dccfc7611b468b1927f9fd5cfdea73bb8d5
B2 sramtestvehicleg4 7576×107767576, 10776 1.5 MB08fb413f3934c535bdde39281e84004e58bbb7e3841c4ef79b95a0f2d86af5bb
B3 reram_crossbar_rerun 7576×1077615152, 10776 1.7 MB73aeb4bf1185a98ee8b15e2db2f8ec7b59890a7d884d7de9f8d7fa1957e183ee
B4 tinytapeout_skullart 7576×1077622728, 10776 2.8 MB1b61ade66629c34459fb7e5db89187f59cd63af909803362940d95f782e19568
B5 soomrv__mpw-8_ 7576×1077630304, 10776 5.9 MBba889b512f4a0f9ab95b12bf747ffa3793afa5e165f0a8ff56d9d17ea192b93a
B6 clock_divide_selector 7576×1077637880, 10776 1.6 MB84727a5721e93ade1e8e0ef4cef31f4a0f3c98fe928f6c96f683c272a4d64ac0
B7 reram_module_mpw8 7976×1077645456, 10776 1.6 MB18399c1f1b9121956e380445a774e86dad39168be2489f389bf92d23f1cd3a05
C1 shapingthewaves_8 7576×107760, 21552 3.3 MB046b92ee9ca34d6b41f98ea1f7a45bd432d365edcbd952264cc13e835fba1f72
C2 leosoc 7576×107767576, 21552 2.6 MB9489a0853959cadbfee36845653c28e957abd08e5fecf102dfcd34ca2055462f
C3 decrypt_aes128 7576×1077615152, 21552 2.6 MB14105a1507db44896bf794a0cc1a6fd2170cdf1e4c70eed436c0de128f3ccc03
C4 approximate_adder_axha 7576×1077622728, 21552 1.6 MB52d3684523c1cd673c31355bf905a2388f0e25ce08699f0a60d5808328ba6da9
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 riscduino-pxt1 7576×1077637880, 21552 2.6 MBd5886ed59b2fd5ef7a370643114cf87940d4b8cbc38f9c6ad9ad0111ff52aebb
C7 fitbit_project_using_openfasoc 7976×1077645456, 21552 1.6 MB214a2f08b84d3e0a832042c9a5c8b0f3e9ef6f8b29e5180de94c0072fbd85bb8
D1 rift2go_2320_sky130_mpw8 7576×107760, 32328 5.9 MB035f1870d5595866be188e1b7e62f0bf405865628d1b0ab63d5df57df63e0e4f
D2 hyperram_controller_for_sky130 7576×107767576, 32328 1.7 MB692d84da952b1a4aafb2252221edff4b896f718c75c7dc5c872a6bc45d211e50
D3 hardened_alu 7576×1077615152, 32328 1.7 MBc3611e41ae2606f45a410cccfb5ecec16bf3b609676fe4e7636913d5a2f928e8
D4 an_open_source_hitachi_sh2_for_motor_control_apps 7576×1077622728, 32328 2.9 MB5e1f9f6f4a7a864f50eb8b19337639fa2369bd4d8ed5e60e573b90085cd96673
D5 mixed_signal_circuits_mpw8_dec14 7576×1077630304, 32328 1.5 MBc2e40a206d4b6aaea3cb2f1e6a456389c06603b5b0d2acd70beebe7f61f983b0
D6 gf180_vs_sky130 7576×1077637880, 32328 2.4 MB7deac600357204c489c9ddcfa4360322fa949e31b4e4f6cee0cdbd0a55a84f99
D7 iiitb_tlc_mpw8 7976×1077645456, 32328 1.6 MB20bcdae37f93ab1f423c127cbfb768246e2baa48e6eefac35fb3f3412d1017f5
E1 iiitb_sd_mpw8 7576×107760, 43104 1.6 MBe02ca1cb6135c512145c741369ffd181f875b33428ea18e4dd8d20c437997503
E2 iiitb_sfifo 7576×107767576, 43104 1.6 MB8499a1bfb3fa07501e10c83fc6cdbd01520fbffc64ffe603e270d8e5753a7cc3
E3 iiitb_alu 7576×1077615152, 43104 1.6 MBb83768d75650a6dab8f1c26c1929610d742744fa3dbc0303b015fb5444c2f3a8
E4 ppcpu2 7576×1077622728, 43104 4.3 MB8770ca33b8f624f5ab2629695f3a85a58883bf515293c77478e6dc03cb38f20d
E5 mega4_reram 7576×1077630304, 43104 1.9 MBdd7047288bf2d537911395574bcbf37f3281aa6031b04cccb269bd4ea7716b4b
E6 tiny_user_project_vgaclock_mpw8 7576×1077637880, 43104 1.6 MB740c0bb8e6784078b048a15c5752bbe1c4589637f8d0316a3eecb306320ee226
E7 sky130cla 7976×1077645456, 43104 1.6 MB0f3fa207e414d8c89fe5afb16d8db55f0f1c23e8a2392304818c76f6fd6a33bb
F1 uetrv_esoc_v2 7576×111760, 53880 2.3 MB8670c3202f59b586245e53020e110fdbf3be404a05506a4cfa2331c99066d2ad
F2 sequencedetection1010 7576×111767576, 53880 1.6 MBff1d1e565f578301c927dc1d6d33665b28830cc7eb1a37206d1203329714c8dd
F3 testasynctrimux-mpw8 7576×1117615152, 53880 1.6 MBa5893b3ccb354f0a1c30ace03b67c1123bf639b537806217324862c13b2892f8
F4 iit_indore_dadda_multiplier_mpw8 7576×1117622728, 53880 1.6 MBf1321f6006dd4313f9c4ded34f976d175b46ca88ecce30ef1721086cad6b353c
F5 modified_baugh_wooley_multiplier 7576×1117630304, 53880 1.6 MB2f59f2f047f966d69474aba20494b7dea3472eb7e3a0a606bdb8ac66a1247ee9
F6 arbiter_puf 7576×1117637880, 53880 1.6 MB54c19815b5c07c46ce918579e380c2fe07c65a36eed40ae8d345f6f8fe42339a
F7 unigate-sky 7976×1117645456, 53880 2.5 MBdefa29c95d880e5d8148762dcf92c2227aae54cf367ddd1243f3e8b88d4817f2

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 NPCM on mpw-008

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

Mask layer
NPCM — Nitride Poly Cut
Process step
78 — Nitride poly cut mask
Drawn layer
95:20
Layer on the mask-layer GDS
49:0
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.