mpw-002 / NCM N-Core Implant

the NCM shapes of all of mpw-002

40 of 40 dies rendered.

113,097 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 (6.8 MB in total, largest 417.0 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-002_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-002_NCM_reticle.png
the stitched reticle, full resolution
5.3 MB 397a6e0d2a2c52782c3371c003153a4ea17a75046a1c685dce674b4c12cb627988a6ed9b 22e7e6a7b0a49e480fdb8d4de0f45633dd020e615c77cb6f08c5a85a313b0bfa
mpw-002_NCM_reticle_overview.png
the same image scaled to fit 4096 px
452.4 kB 496b291660736ab84d25f6baab56a78c04295e3937a7f24f3efdb85e4b9291654a12d09a 996ce5e4b7c577f0af82ec3f01020656b3f6b49098ec87a552b4fdea5036b88b
mpw-002_NCM_tiles.json
where every tile belongs, and its checksum
13.2 kB 0d447d661d71dc2a7dbc4344987cfeeb0ebc1fbb02bdac1bc7db9bf65147256508a3c9ab 37cfef1cdb8dd04e762e66fc6d49b1ba7b10dd701d981370f207872e5a9ecefa
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, 0 146.3 kB09440e7b9b0043a8c559d0449c374c9a7afe562debd7b3c2063637e040ded647
A2 wishbone_can 7576×107767576, 0 148.7 kB14b1131707fcee2d1a68ce8b90567142e88f588e2e936093c77b096f261fab97
A3 Analog-Neural-Network 7576×1077615152, 0 139.4 kBa9f3cae2562913c59b5c1a289ab555f77045e0b0a339131c9b34d7b9841d8708
A4 caravel_dsp2 7576×1077622728, 0 145.3 kB9dd0e937d307d165b288ff683d82970a8ac0b0951edc4c32828e4a850c82f74f
A5 eFPGA_v3_caravel 7576×1077630304, 0 293.0 kBc77ddfd68c7849417ae636a3e23863ac9baaef802e67507dbf3308a67dd2b9fc
A6 opencryo_testchip 7576×1077637880, 0 139.3 kB549d0da1acdd8aa1e7d062710d54f81767173e74ee7fee124d2b2cf17256549c
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 yiFive 7576×107760, 10776 157.7 kBa0147a79eb8c034225c2397ac900a155aef4372df63728ef722c2e6056c242fb
B2 lexicon 7576×107767576, 10776 165.3 kB7af7dd10635302b6c15eecd57dd5cfdddd9226240b93b3b3fb93a7a2f3c71757
B3 ucsc_openram_test_chip_v2 7576×1077615152, 10776 185.0 kB319cc3838050d83b28e9e4bc5fdaa9a43b8f7a21114bc85ec959a47daeadab66
B4 yonga-lz4_decoder 7576×1077622728, 10776 145.8 kB8bed60bd8331f4758322ba9a80fe8feff15b8d9e3a50d92850234dc109a9bf94
B5 Potentiometric_Digit 7576×1077630304, 10776 191.1 kB6926b39484a7f2773c60e1c58a3f3a968a05a05f01e2f76f2c6d2bddf60696a1
B6 fuserisc_ver2 7576×1077637880, 10776 268.4 kBaeafaef0350e742131869a7a1085bf41a0f591bea396f4d4ff5a17db4bd4e3cc
B7 amsat_txrx_ic_mpw2 7976×1077645456, 10776 147.3 kB638862db88d2954728f9d73ce79b0de33a860055be4d844d8dbb32ee4deb7672
C1 Comparator_3v3 7576×107760, 21552 139.2 kB8dbd4c6856efdbc8b067a3564d71996564ef5e2261b08dc78584210502469eff
C2 caravel_multi_encode 7576×107767576, 21552 146.0 kB1c726254e0e061502e09b2e9abc02a64ff981fdd9b7e60411ef1f0179643c73d
C3 kasirgalabs_uart 7576×1077615152, 21552 144.1 kBece7fe72b50c77036d615ea7ba0d6fdbd8c3ffdd4af8b80dbb398a9de9087b9e
C4 Automatically_genera 7576×1077622728, 21552 142.7 kBcc41cbd7bdbcde935d4e5e2510d6aa0fab6dd4744f9b30a9fe934d65d9bb4fde
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 uqab 7576×1077637880, 21552 179.9 kBc8534a11839c7266f6cd6065744443135ca543ad1242797f02dee1d42f1b8b08
C7 caravel_azadi_soc 7976×1077645456, 21552 166.9 kBcedc366ffc6ba95c41185f13895d9042fb873dbcb854177f0d44c5f6c93c3a67
D1 caravel_dsc 7576×107760, 32328 145.7 kB9f6126011c5c1bc4ba1b698cee5c142b15632d9017a2702549e8fead77e0ea4f
D2 SOFA-Plus-eFPGA 7576×107767576, 32328 417.0 kB6a115f21d2b1b0c8eb687473179e92006638cfc848e818a235168a9122566a6c
D3 caravel_user_project 7576×1077615152, 32328 144.1 kBece7fe72b50c77036d615ea7ba0d6fdbd8c3ffdd4af8b80dbb398a9de9087b9e
D4 General_Purpose_Band 7576×1077622728, 32328 141.5 kB12ff7a34a5cfe74f09f6e2305f74d5cdfa2f0bd706b9486c961e978e0ce52db6
D5 zero_to_asic 7576×1077630304, 32328 156.1 kBd7a69e1514f5770157eb6823f363634ba5aaa8844e9557592d97fd6245c12b69
D6 fast_gcd_for_large_i 7576×1077637880, 32328 155.1 kB06dcb96dd5c3d3e742c34d83d0aee0b99f6c3c3434e358ec81ebd915d5cab292
D7 Columbus 7976×1077645456, 32328 143.9 kBcb32e96819ea3087b2ffcede4c0e9cd5425a9124357b348e8fe56a624f718a71
E1 Space_shuttle 7576×107760, 43104 147.7 kBa98d5e64ac9ffdc301e9cbb0da2c559eb5711531a884614d85847d031bbfe85c
E2 subservient 7576×107767576, 43104 144.2 kB46dbccc710e1a52123a001ae9424f4731fbd86ad504a8624bf2462e43ea97ee2
E3 caravel_analog_fulgor 7576×1077615152, 43104 140.7 kBde1ea0595a31dbdc2e906de829dcfcc22d258d461a9e82ae5384aca35d8edbae
E4 bandgap_reference_de 7576×1077622728, 43104 141.5 kB0357eca3e57b96b40304e1a04aa2f5379f5f84e875f711e15714b11ce0e0f9a0
E5 renml 7576×1077630304, 43104 168.5 kB4d368d228100db3cc1a3ddcc1113322aa95198b3ba6ad542fd6e875466d7b5a9
E6 io_expander 7576×1077637880, 43104 142.2 kBf74c730dc7b3914284cfc43b67daf8aee29fb7e6b07d0dcaff202a8401d0cb21
E7 digital_pll 7976×1077645456, 43104 146.5 kBa76dfd7cb407160b4be469ebc19aa5f87ac9bee07a7194d2a5e13375c5b8feec
F1 zero_to_asic 7576×111760, 53880 160.0 kB554edeaeb057357e2d4f277e66a3547b402b39f5c63647af7e4b1db62c216619
F2 caravel_fpu 7576×111767576, 53880 147.9 kBaef928cd8a19d89073ab9760ef3a44be5f35f712172bad8de2744cfd9ce1f425
F3 BrqRV_EB1 7576×1117615152, 53880 184.4 kB0053f333ac89108386a812d41abe5451d0dab120c3f323afac998f59f49280c9
F4 hilas 7576×1117622728, 53880 143.3 kB4a8bda242e6fa95fa5a1c2d7981ab40f447c54a9cad0a3c99f13fd19c88aa6a2
F5 vlsi-sky130-analog-c 7576×1117630304, 53880 143.1 kB2b091606759b106766e3172b2cc9f65565d3b2be1184d964c93e8fe2f69a3cba
F6 sha1_engine 7576×1117637880, 53880 149.0 kBf2682e1031d11f30c61aa427ea9510d6e46d79c9b5f0b4f8d875c7e6762ee1f9
F7 caravan_openfasoc 7976×1117645456, 53880 176.2 kBfe82bbfaf5bb05b4e1b09a49889c23c23e305023847cd901d22baf0a4b7cb5fc

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-002

Resolved: reticle 5CS8007AC, run mpw-002, 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-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.