mpw-008 / NSDM N+ Implant

the NSDM shapes of all of mpw-008

40 of 40 dies rendered.

47,492,651 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 (60.2 MB in total, largest 3.4 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-008_NSDM_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_NSDM_reticle.png
the stitched reticle, full resolution
50.1 MB c88627d14a8cad4fa96e5b87c4392f624c6d0c1f4e78eb71e6327ef7bd9fa95aae749584 768e6f1b7b81ea9df638529a0b2172ad23b52d1e5d737fb6f4cad54ee0591f84
mpw-008_NSDM_reticle_overview.png
the same image scaled to fit 4096 px
2.3 MB 46443aff499596ee4c90a9c5f3bf33a35cd0f651710b5602b32dd50bb6aa013676a8e04b 30142d1ccc936cfe2ddb1e5ef9385e64e97d995cf65dfa962f8d74251379e27d
mpw-008_NSDM_tiles.json
where every tile belongs, and its checksum
13.5 kB 7f0d10766253dd787f616b721e4967b94cb2fbff6e03bdc0aa588d093256680da27032ad 1125e1bbbafbfaab22e9f2e83c68c1b92d065c2066a06ebcf02bd0d415b5ee69
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 1.6 MB00ca6cda55b9637eb1fe607a8a0a5e14cc96eddd64472f499ac2c3861c57e677
A2 iit_indore_mm 7576×107767576, 0 1.1 MB711e81eeeee91d313385c36da3140410ffdcbc0054715e8d1f8f8571f4e46389
A3 energy_efficient_sum-of-products_circuit 7576×1077615152, 0 1.1 MB4f0b838b444e92149923b893209f5314c25acabb24b48e8d2945890d41a2e285
A4 riscduino-dcore_d4_ 7576×1077622728, 0 2.5 MB273c1af35038575024529bf25a1813144dd58fdc604a3e533e0c85d21d1ac782
A5 riscduino-qcore_q3_ 7576×1077630304, 0 2.9 MBa6cd6e8762059b0ad229a258e7c381fd2c8139ced46962d76e19d4643d25906d
A6 caravel_mpw8 7576×1077637880, 0 1.2 MB0fb903cad79bfe7b900d09ca3b02458c2ec9c0c238aa97cb0748e4520d68ddfb
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 nanofabrication_project_using_openfasoc_mpw8 7576×107760, 10776 1.2 MB59c25223fdfc60a35817898efd787aabfb9954a5d481e0f3e838079ac2d1c896
B2 sramtestvehicleg4 7576×107767576, 10776 1.0 MBdaf1450eb92e7a7a3741fbd5920c648cb5494f80553966850ce579dd9059519a
B3 reram_crossbar_rerun 7576×1077615152, 10776 1.2 MBf1beb24fd1f8657d97b34f2c5f05be7bd85d42bf7998cfb335a2e5e641999e95
B4 tinytapeout_skullart 7576×1077622728, 10776 1.8 MB9d15eadddc644c18f27f4d093219da576cf3e3f7046cf7b49528dd98b52d0e77
B5 soomrv__mpw-8_ 7576×1077630304, 10776 3.4 MB125ead830df985945147aa1572fff38b4c6089223cc744a7f4389fb553d720bc
B6 clock_divide_selector 7576×1077637880, 10776 972.5 kBeeab0aacdaca7e35045edc7dbaeb4003753bf21acb71fe1ec250ee5ba2344c13
B7 reram_module_mpw8 7976×1077645456, 10776 1.0 MB898f473a2e75221e252f9edd31ad8ab241a14c79cd182fb8d34b7c5861843b9a
C1 shapingthewaves_8 7576×107760, 21552 2.2 MBc12f2a7d9f50400b6c5a683c6529f27d2e915ce81ed44ca8437f05c39320007e
C2 leosoc 7576×107767576, 21552 1.9 MBf0876110bd9d154dc6a7048dcd56e774987952e9bbd6f36a92ca386e91b4de94
C3 decrypt_aes128 7576×1077615152, 21552 1.7 MBaaaae07c4a009a45b3d2b6a4f24aa63b98f861c72e2ebed0ecd9153caf316a33
C4 approximate_adder_axha 7576×1077622728, 21552 1.1 MB809b81226be0c21f901027e6e2dced46719700d7cf06af5639d03969f1e4e39d
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 riscduino-pxt1 7576×1077637880, 21552 1.7 MB66a9662ce9d791bd83f6c96fa790c0a484b777dab7b263029ebcbdc76081563e
C7 fitbit_project_using_openfasoc 7976×1077645456, 21552 1.0 MBaeba4841e765c3df61dd863ac1e3073fa5fc1f305806f39ce907d52741f896d0
D1 rift2go_2320_sky130_mpw8 7576×107760, 32328 3.4 MBe059b917305f19ac2bfb477241a28eea1aed9719414c7578ff6be931e24d6e79
D2 hyperram_controller_for_sky130 7576×107767576, 32328 1.1 MB24bfcebede8c523fe26caf4d8029a09a95409adf707cf0d76d606544b68ea4bb
D3 hardened_alu 7576×1077615152, 32328 1.3 MB1c4bc61d5d2421cb4fd6d572f42224d04aa109fd2fa999732db4c44ec4bcd1ef
D4 an_open_source_hitachi_sh2_for_motor_control_apps 7576×1077622728, 32328 2.1 MBbde5cada774e1a288567ee4a011e703e01484155c700874e39835f43010d7562
D5 mixed_signal_circuits_mpw8_dec14 7576×1077630304, 32328 977.7 kB6579f4ad3ea36c6c2b9d23b7bbc2bfec4e1fdbda6a9e928e1108503b3ec4544e
D6 gf180_vs_sky130 7576×1077637880, 32328 1.7 MB580e9194914e2fae176c5f85a67faceab903e786525c93046271528f2db46a3d
D7 iiitb_tlc_mpw8 7976×1077645456, 32328 1.1 MB8f8fc11efc2d535b34b38ba7f01564e2ac2c74698be39c9abec948b523e2e78b
E1 iiitb_sd_mpw8 7576×107760, 43104 1.1 MB057dcf9faf8bbcf9533fc0c58fff4fb51ff6386828ecf573ec1c083f3526e539
E2 iiitb_sfifo 7576×107767576, 43104 1.1 MB528dd434c0389f7a8120c0bc612dd150928af7e7a1c481cd7cf780f2caaa4fa7
E3 iiitb_alu 7576×1077615152, 43104 1.1 MB613e4cdd31705cf6cce7c7d8e983dbde6d96746e782b97bb4420f1a7fdec46d2
E4 ppcpu2 7576×1077622728, 43104 2.6 MB0eec6ae23055506a961616a96d7925f596ba1ff02c4b38b2b2a1e23ded2266d3
E5 mega4_reram 7576×1077630304, 43104 1.1 MBb48d1392c19f804c9b8db9c322fe09e4d36f2ee5058244917ff9ea53d6a01bed
E6 tiny_user_project_vgaclock_mpw8 7576×1077637880, 43104 1.0 MB2112cb89ea20c7549b157ec49932bd6ff790d4f3d843c740161a194476e6309a
E7 sky130cla 7976×1077645456, 43104 1.0 MBb76139acf6b821167b21e071310e2a7e395409096d1ad0f7d3dd868df12c2632
F1 uetrv_esoc_v2 7576×111760, 53880 1.5 MB47f022855d14ce5c90b2699b7e854c7d8c67bab12485f351d697a5cbf366f622
F2 sequencedetection1010 7576×111767576, 53880 1.1 MBb1b9424b0d811919ac277302ef7f250cdca6d1a8a91498f8eab1ba7281e56490
F3 testasynctrimux-mpw8 7576×1117615152, 53880 1.0 MB0d4ef5034c82aa373ed679947ff7c1137ac87f668c0f776dfc76e27c9392c37b
F4 iit_indore_dadda_multiplier_mpw8 7576×1117622728, 53880 1.1 MB9f6ad5aea415782774a38978dcbbd793558866569a7a7d7fe0694676e40ab1a9
F5 modified_baugh_wooley_multiplier 7576×1117630304, 53880 1.1 MBda98292e1a77982ffe4e60546d1a7a3461662d89102b0c8f07c956a2173d7215
F6 arbiter_puf 7576×1117637880, 53880 1.1 MBc1b21441b2045b5b2a9a31dc79ed9ac0642ec2a9aa5103b0013b552ba84582ed
F7 unigate-sky 7976×1117645456, 53880 1.7 MBfa4d3a0eb8f3d5491f4819b9aa49be625ee7409f4bb2c17c472c13d28a8dfdeb

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 NSDM on mpw-008

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

Mask layer
NSDM — N+ Implant
Process step
85 — N+ source drain implant mask
Drawn layer
93:44
Layer on the mask-layer GDS
30:0
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.