mpw-002 / NWM N-Well*

the NWM shapes of all of mpw-002

40 of 40 dies rendered.

29,543,119 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 (23.8 MB in total, largest 1.9 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-002_NWM_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-002_NWM_reticle.png
the stitched reticle, full resolution
16.6 MB 01a5d43f893f1696dfd8131e104c6d4d5fe51b429e46770e9f33bb9a4da7ac6e5d1359e1 d091f15644c911abbf5700d6ef3cf57dc80ecff6714db38bfa769eacf4f387d8
mpw-002_NWM_reticle_overview.png
the same image scaled to fit 4096 px
1.6 MB 7bfcccb12e54e5daa141f1841e2c5d9e153f93cd0fb3e2a7c96bc725fbf8a48f4f790f2c aece46e7c4a4780508a5e3f82777b7a1cd18d5559722615a5387a2beae4e12df
mpw-002_NWM_tiles.json
where every tile belongs, and its checksum
13.2 kB fbcca163358bd8522b2636919cdd251de558f9385cea0d280142284b19999e8fb5273e67 694fd81a994b4c99ec6850d54c186a3ce1f7505cf66c02cd0e4e42d0379b0343
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 axi_dma_using_spinal 7576×107760, 0 552.0 kBf9971313761c7ef99c5510a7f7a329631ce214662d0143a98f71aa6b00426b3b
A2 wishbone_can 7576×107767576, 0 528.5 kB228f6db9f3ffbeccf6ecd99bedb82f05f8a02148036c38821c825731cff81053
A3 Analog-Neural-Network 7576×1077615152, 0 381.3 kB71f4d98f00810e6e8bbbb69fd5897e5b0f9270afd4d9cdc7f5b16c0c1051424f
A4 caravel_dsp2 7576×1077622728, 0 466.1 kB77dcd61d4bda03a3f72b9f88c0416ba9bf18e84be1171d165d4cf6d63f01c91d
A5 eFPGA_v3_caravel 7576×1077630304, 0 1.1 MB007703e00f8f63ae90c7575846bca93c4f0a4d879ded74dac47236dab36f3c79
A6 opencryo_testchip 7576×1077637880, 0 380.0 kBb96f226bb63d2bcbaa43e97376da1e0b2a21fbb336be983e89af5bd291db3603
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 yiFive 7576×107760, 10776 668.7 kBfc8cba403ca51cc4fb72a90638585586cb78702dbb6592cb5435858b289f90ef
B2 lexicon 7576×107767576, 10776 666.2 kB4fc522ddd7e7a358ef41dc89c369b9ee13c6843839abe8db05ae4473859a2566
B3 ucsc_openram_test_chip_v2 7576×1077615152, 10776 572.7 kB1b3bdbd0a13b3398035831879d9083384f880872a9590ffaf937679b95e575b1
B4 yonga-lz4_decoder 7576×1077622728, 10776 464.1 kBfb2d14b415cb81384ca71717895fa66496600e674d098bc3a89eba7c32d5d87c
B5 Potentiometric_Digit 7576×1077630304, 10776 407.0 kBeddb949d984534fd9ec626d616d5de6261d92bfe0e9ef9f992a815c3f671514b
B6 fuserisc_ver2 7576×1077637880, 10776 1.1 MBde03ae2a3ac3cd5a8837f572e2bc0466007d9944419109402bda6a0f1c58b408
B7 amsat_txrx_ic_mpw2 7976×1077645456, 10776 386.4 kB876ff8bd87984d5b3b3ee38138ccb414c18e6f2f37df41c6aa6a9d04ddfd6881
C1 Comparator_3v3 7576×107760, 21552 379.9 kBff27caa655b9d01daea0cbaf34fd5c7317545146c911f4062baa228c3ccacd4a
C2 caravel_multi_encode 7576×107767576, 21552 446.1 kB14a14f83d282e2c22c4499687cb24d48de7587841516c3b223c2ff3d33508a36
C3 kasirgalabs_uart 7576×1077615152, 21552 422.7 kB843d5ca29f81b0c29137f8690b65e479fa1f35f26130815dbb3cfb7734b53116
C4 Automatically_genera 7576×1077622728, 21552 419.4 kBb18c2fa399e9acd0c2f5bb0d7d7e8317dcc81ba1d1211c35bcf3cdee3d7ac465
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 uqab 7576×1077637880, 21552 916.7 kB225ecde300f7ee640917e2397649cc969dc2ba2db6668f4b2c33bda9ffcd3897
C7 caravel_azadi_soc 7976×1077645456, 21552 691.8 kBc0b53f16403f5fd923871975ec951eb1a7403738c7f0ee560a4fc6a2d6c0ae05
D1 caravel_dsc 7576×107760, 32328 447.2 kBc71fde1e500c9331992856d4f4dfc9356393b0039f30aac45bae5ad1bbb101f0
D2 SOFA-Plus-eFPGA 7576×107767576, 32328 1.0 MBfee70aa123ad8f78460a09f7e2ccae21897a0ffb2bc7c28ec8bac07484ffb500
D3 caravel_user_project 7576×1077615152, 32328 396.4 kB5ddb9a04637d6775d15153c528d9a70bb3c0fa27d410626ba6654c62f77db45c
D4 General_Purpose_Band 7576×1077622728, 32328 390.1 kBc9818dda48514f989fdb5922aa2ea3b55ed3c1c949f5b63a85a682c112b282f6
D5 zero_to_asic 7576×1077630304, 32328 558.0 kBd591b125b3cc41698b17ebf1c1c6d42ea89604fea98fb65eeca9c2e9283fee93
D6 fast_gcd_for_large_i 7576×1077637880, 32328 1.9 MB0620d7c75faa13da63a6e40f372e0f5755de1b3bd2a7165aa75f281f0a2c6a24
D7 Columbus 7976×1077645456, 32328 392.7 kB951169315ff8abaab3e7aaf30202e5bb0ac26dbdbe69f5b6546b64b8f19ea525
E1 Space_shuttle 7576×107760, 43104 656.1 kBad7d78955aa556b01f1ddd8cebbc63c954be6b9529034ae1e19ef84018dbbee3
E2 subservient 7576×107767576, 43104 473.9 kBff6fc145773a850dd8484dbf880372b77ae718358d6f54feaaa5bb38effc8596
E3 caravel_analog_fulgor 7576×1077615152, 43104 389.8 kB1ce306ae1f7aee099b448fc1f616e1bb6045d7e0d1a08752d71ca142e94d6223
E4 bandgap_reference_de 7576×1077622728, 43104 390.1 kBb3e8afe1c91e3cf5054383f1d03b912e40049d0729332f35a8331440fb3a5b0d
E5 renml 7576×1077630304, 43104 837.9 kBdf80b731b7bb1e3661d461f0c2776a3e32a452c07037dc18e457d5ce37b7d994
E6 io_expander 7576×1077637880, 43104 421.3 kB2d92a6a82cd734de483f4278aca945d3faa117d6d1d1145120a6ff03f65c0208
E7 digital_pll 7976×1077645456, 43104 394.4 kB8c6e25ef802fcef6b6b07ffc384ba62cd495c51dbd63ca524ba957f29519c3cd
F1 zero_to_asic 7576×111760, 53880 601.3 kB7fa1e8b3393e51845568705a82cde310873a29ac0d4afa638936b1204558173d
F2 caravel_fpu 7576×111767576, 53880 442.4 kB3681d6d934a4f7ac184b3d25cf8eb9a0ffb73622d0ac5976e5356d75b58f6938
F3 BrqRV_EB1 7576×1117615152, 53880 1.1 MB54f1c26d0cb9d6c46cbbae989489a61820bee754ad15661ee5c691905601a7a5
F4 hilas 7576×1117622728, 53880 386.8 kB8cc45a92976552701d5a1c45109dfeddc75c9c0eafba344f9a0ff90da781d2dc
F5 vlsi-sky130-analog-c 7576×1117630304, 53880 383.9 kB50dd1d030b62469859caf15d70ec850d8357ff9cdf49a797c4fa14ba27fe97ee
F6 sha1_engine 7576×1117637880, 53880 487.5 kB29c1dd0192fa311bcc7a6fe2d8328cc0eee084057978123473a96a277d9f3d01
F7 caravan_openfasoc 7976×1117645456, 53880 616.5 kB882eacf49b060e43132f92d241ab2be09c704776e0760e882e5777ccc5522631

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 NWM on mpw-002

Resolved: reticle 5CS8007AC, run mpw-002, mask NWM

Mask layer
NWM — N-Well*
Process step
17 — N-well mask
Drawn layer
64:20
Layer on the mask-layer GDS
21:0
Detail
NWM = nwell sized (cnwm.3a outside hvi / 3b inside), with DEPMOS/pwell-resistor exemptions
Used in SKY130
yes

mpw-002 — SKY130 MPW-2

Foundry product
EF MPW#2
Reticle set
5CS8007AC
Run date
2021-06-18
Submissions closed
2021-06-18
Projects
56
Fab lot
4205819
Identification
confirmed — Lot records: EF MPW#2, lot 4205819 = 'SKY130 MPW 2'
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-2 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-002/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.