mpw-008 / NCM N-Core Implant

the NCM shapes of all of mpw-008

40 of 40 dies rendered.

122,768 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 (6.7 MB in total, largest 222.4 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-008_NCM_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_NCM_reticle.png
the stitched reticle, full resolution
5.0 MB c396d639311ffd2b4464d173ec520fb05fe2442cdb17cd81511cab2cd8d0d90e5fb73f02 961b3757f792fc7a6d5f71e5bbd6dcbbc4bf9da35f0dd1f022c9bf5999056bfd
mpw-008_NCM_reticle_overview.png
the same image scaled to fit 4096 px
456.4 kB b7b7c768537449cf6fdf3b23f9076161474eaa24de85ff5ce5a9ce00e28eaf6ae56f28f0 a9a9c057c6ec7e90ea801f7506d64ccb09389e07279ee68f3aa0876640b4321c
mpw-008_NCM_tiles.json
where every tile belongs, and its checksum
13.4 kB 991acf087e62e8b3e60d9536e339ccd158583ee2ec9f4e69814d2d7ad576725382eb61a4 ed4910bf8229c4f65f7d6552c83cb7d7b4003e4810fdd6de022b4e21c2c82008
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, 0 153.3 kB47e6b0dcc09b999edd38495c1d66f89f3704c592e9eafde5a8935c1336f06b37
A2 iit_indore_mm 7576×107767576, 0 148.9 kB7c417af55ec019d64ad3f0fc9373c8e942d5ac58b5be8486b16fb4d68bcc5976
A3 energy_efficient_sum-of-products_circuit 7576×1077615152, 0 149.7 kB5750a8d4b3a2fc36a7d556951e63c3bc79de47d808c28a901a474a6555d0f73a
A4 riscduino-dcore_d4_ 7576×1077622728, 0 201.2 kBc4b74792936e50af4cba635f25ba485341305e1ed26ec8e0f8b56df6614648f8
A5 riscduino-qcore_q3_ 7576×1077630304, 0 207.5 kB576ebb910d597196a755a6cc894591d8a9bd26df11d3bfad586030e6a2b35056
A6 caravel_mpw8 7576×1077637880, 0 149.7 kB5750a8d4b3a2fc36a7d556951e63c3bc79de47d808c28a901a474a6555d0f73a
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 nanofabrication_project_using_openfasoc_mpw8 7576×107760, 10776 161.6 kB92902bc3cbd8dc56359972c47656f98734c7b2fdff6673dcff8e6d071e2c7995
B2 sramtestvehicleg4 7576×107767576, 10776 153.1 kBea987683e1d8472b83bddbdc4d777d52c53a68995ea970023acbb6e5a2998afe
B3 reram_crossbar_rerun 7576×1077615152, 10776 162.5 kBb13838d5a21f49dcfc896e1a1d24fe7ca62452c47cb10633c0b02e65d9f0761a
B4 tinytapeout_skullart 7576×1077622728, 10776 222.4 kB5dab0cc3d4eddd18f78f3a8e8bf77f46e785bd816cf61e73af93b75cf7f6684c
B5 soomrv__mpw-8_ 7576×1077630304, 10776 178.6 kB18ca3e9b52eb5086eb93e6b5d027e5f6f1eed0f63a5233741394d1640fa2c77d
B6 clock_divide_selector 7576×1077637880, 10776 147.5 kB1553bcbc1f6a5444f3a1c98f197c7d93217e901a67a597c14b847c8a800a7d2c
B7 reram_module_mpw8 7976×1077645456, 10776 148.7 kBf2a67779bb73c468a710040c44bb8ca47fbb6c4a374644fa4d3df233625a711e
C1 shapingthewaves_8 7576×107760, 21552 184.9 kB7d5b1d4cd3be341a5444f2d00165099d0c59ed3a038e416855a1b91411856067
C2 leosoc 7576×107767576, 21552 200.0 kB6d1732ab53d7d35a62289e1a9c2522fd206049334a59f0b676279a30f305342f
C3 decrypt_aes128 7576×1077615152, 21552 152.9 kBb91b7eb3350cdbd3505ec3ee21cb380b681f3db4568f429a012626dab66e115e
C4 approximate_adder_axha 7576×1077622728, 21552 149.7 kB5750a8d4b3a2fc36a7d556951e63c3bc79de47d808c28a901a474a6555d0f73a
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 riscduino-pxt1 7576×1077637880, 21552 171.9 kB487b36137542c95dc83a7a423190da0f4bda5ebe76dd30405affe364da8f3ce6
C7 fitbit_project_using_openfasoc 7976×1077645456, 21552 153.1 kBd01bc24bf117e089b23d251a1ebc1dd546859fdb46bed5db18597697fe8b1b21
D1 rift2go_2320_sky130_mpw8 7576×107760, 32328 159.7 kB3b633d1737addf2142d3a90e4e5df912f88f84aa45e16856cdc841a6474c0b70
D2 hyperram_controller_for_sky130 7576×107767576, 32328 149.2 kBaaec2ab523a0f333976cd767761cbd784f83fd37bc55fba3037f76490fbf5e4a
D3 hardened_alu 7576×1077615152, 32328 156.5 kB87c8c7c7ce6504c479307c4e772ec6f34acc757e8cee7cbf4af8e0e653d4b66c
D4 an_open_source_hitachi_sh2_for_motor_control_apps 7576×1077622728, 32328 203.5 kB9ba1d3090ce7c20c0595bb61230c7817090441ced2b50ecd7e48f2cad17abb53
D5 mixed_signal_circuits_mpw8_dec14 7576×1077630304, 32328 144.7 kBe02c2ceac9ce14b8ec13f2cafef028dd3086803787cb32336fe17141056944aa
D6 gf180_vs_sky130 7576×1077637880, 32328 157.1 kBf33ad69bc0509ebeaedccbd37e8eeb091deb494144764551f6246ae93c996cae
D7 iiitb_tlc_mpw8 7976×1077645456, 32328 153.7 kB6b172003bc77f2673bab1bee8095ef1fc70a34b41f5c392d1a470ff226cf9402
E1 iiitb_sd_mpw8 7576×107760, 43104 149.7 kB5750a8d4b3a2fc36a7d556951e63c3bc79de47d808c28a901a474a6555d0f73a
E2 iiitb_sfifo 7576×107767576, 43104 149.7 kB5750a8d4b3a2fc36a7d556951e63c3bc79de47d808c28a901a474a6555d0f73a
E3 iiitb_alu 7576×1077615152, 43104 149.7 kB5750a8d4b3a2fc36a7d556951e63c3bc79de47d808c28a901a474a6555d0f73a
E4 ppcpu2 7576×1077622728, 43104 169.5 kB38811ac05729449dd476d13e3ad4b608e05a67e896ffca8923338f5a9a485016
E5 mega4_reram 7576×1077630304, 43104 153.2 kBfc403ecede041939d02b4f1357b7e770028f51c133c63a8d1269e6c941ee5aa9
E6 tiny_user_project_vgaclock_mpw8 7576×1077637880, 43104 147.8 kB97d27846f960c0d79f4b5d9e614e4a3b97c6288760bc96642592da1d75ec1567
E7 sky130cla 7976×1077645456, 43104 153.3 kB7a4bb3a28618379cd11d456605c96067e66ccac48ff4d8afffba6ee027b811c6
F1 uetrv_esoc_v2 7576×111760, 53880 172.0 kBc6d4ac30bdd0421b6ed5327291a2c8c19b8853de21dde15a856d358f818205cf
F2 sequencedetection1010 7576×111767576, 53880 153.6 kB2996e1418366e61e4b95e5e506bf1455b1eb0ff7e9bcd8c266672936fa40fe14
F3 testasynctrimux-mpw8 7576×1117615152, 53880 151.7 kBb8aa874487cfbfba5cae0d24714df00bd050a3c8dbc495ff2703ecf6054a492f
F4 iit_indore_dadda_multiplier_mpw8 7576×1117622728, 53880 152.8 kB7262f0216d96756e8bb37ea076e7af93cf2fd4a8e937491fbf3d68d74c34fec3
F5 modified_baugh_wooley_multiplier 7576×1117630304, 53880 153.6 kB2996e1418366e61e4b95e5e506bf1455b1eb0ff7e9bcd8c266672936fa40fe14
F6 arbiter_puf 7576×1117637880, 53880 152.8 kB7262f0216d96756e8bb37ea076e7af93cf2fd4a8e937491fbf3d68d74c34fec3
F7 unigate-sky 7976×1117645456, 53880 163.6 kB461b734abc647a8dd008c71129fa10af0d0c642be65d1b137846f6d2991471d0

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 NCM on mpw-008

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

Mask layer
NCM — N-Core Implant
Drawn layer
92:44
Derived from drawn layers as
92:44 OR ((64:20 NOT 75:20) NOT 125:44)
Layer on the mask-layer GDS
17:0
Detail
drawn ncm in the core plus a created periphery part like HVTPM; only the drawn part is rendered
Used in SKY130
no

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.