mpw-002 / LICM1 Local Intr Cont.1

the LICM1 shapes of all of mpw-002

40 of 40 dies rendered.

423,495,011 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 (176.0 MB in total, largest 13.3 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_LICM1_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_LICM1_reticle.png
the stitched reticle, full resolution
105.2 MB ec1247f4c005e4f12aebed6fc44c16d56e350e1ead2d3f684ddc65c79753845ea8f8adc6 8ec5732c209ba9ae1c1839396d6f8237c31fbb797bf0d4267b8e845dab786ce7
mpw-002_LICM1_reticle_overview.png
the same image scaled to fit 4096 px
1.8 MB f691a6cbe3461f39b155b6eb8020087f7f8d640103352ff96090ecf9ee8eeb9973e02688 41dc85ba058b4ac4514880e5fdd7f31f2b7784735abd03880feeb6d9fa5740f4
mpw-002_LICM1_tiles.json
where every tile belongs, and its checksum
13.4 kB d528d36e7d3667bf50ee695facab7793da5c0da94d362bab08c1a314b9505d7ae73dcb04 02303debe5b7cf1f7966905096f4325d9375f26211236c8b0d760998f2f70440
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 4.2 MB553184a101794a33ad9905123a536554a78b89efd5aa48f4d518224956c21c2f
A2 wishbone_can 7576×107767576, 0 4.2 MB54b628ad7e2561d456b5ac14dfaa34bc0b30fb2e5525b0e8bc2c8ebf0f446565
A3 Analog-Neural-Network 7576×1077615152, 0 2.8 MBcd4461094601af80ff614e83c2d808e317b6edaafb6358c5c844e97633cdface
A4 caravel_dsp2 7576×1077622728, 0 3.6 MB12406e71dbf4bc1ba37b15a30a80f283124746305e34a373652f6147df8bfdb8
A5 eFPGA_v3_caravel 7576×1077630304, 0 8.6 MBb9ba322a950827e18d6d21236396d850336f014fadb5172887f8e46f2f5d1d63
A6 opencryo_testchip 7576×1077637880, 0 2.8 MBeebae34be46e042b97620c0cfae27b95a293cb0d46156793b66eb5cab517d1b5
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 yiFive 7576×107760, 10776 5.1 MBd0e6cf7c2e9eccc10f83e042205bc954b72ab98e7e1c4c241dcbe7c0fa767767
B2 lexicon 7576×107767576, 10776 5.0 MB661c66975f83bf5af579562683e632a0715ba8cfc95aa90146a91ed342c80790
B3 ucsc_openram_test_chip_v2 7576×1077615152, 10776 4.2 MB62163829a06b0d2978c5cd371d1ce30878d4c16cf59c62085b5ba20fa74e56cc
B4 yonga-lz4_decoder 7576×1077622728, 10776 3.3 MB5bf863c7e3239ecb51c52e772f88d7df041f05acbdb38e8af3bb19a52e4f43ad
B5 Potentiometric_Digit 7576×1077630304, 10776 2.9 MBebfb56ebda0b2c56998223da2d722ac9c4b5da6ed73ce42b190792fe2b171a50
B6 fuserisc_ver2 7576×1077637880, 10776 8.5 MB89e4f5043211dd3f872025f3c0cb907b10a31cedac9d6403d319ed84bcd32e9d
B7 amsat_txrx_ic_mpw2 7976×1077645456, 10776 3.1 MB55b2d0b2c7694653dfc6030f89c7cc8f8e46f39a905f23f898f902e343aaa9f9
C1 Comparator_3v3 7576×107760, 21552 2.8 MB0d0cf1d027e00835d137c293d65c422457902336431d1e63595977a6d1ed3f50
C2 caravel_multi_encode 7576×107767576, 21552 3.2 MB71294ae714a4966487338616f46ef8eaee10a85074378d7a8512f31b8cce641a
C3 kasirgalabs_uart 7576×1077615152, 21552 3.0 MBd706035cc1f50df79be71c37584945be208c1c13a9359680a1ccdc980a256b69
C4 Automatically_genera 7576×1077622728, 21552 2.9 MB2986745b306d2e61a40523c7f3bc364c35b39b4f5f7dcd4bc3c7d3c8dfbc4c49
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 uqab 7576×1077637880, 21552 7.5 MBc38908df99bbd83198c01462c3603a42b644df16df2e51520a69f2abc66dc524
C7 caravel_azadi_soc 7976×1077645456, 21552 5.6 MBba1d4e9f583a9ae043ad87e125019c19241980f7ac659fac535060b6a7f12df5
D1 caravel_dsc 7576×107760, 32328 3.8 MB8299bb7b16e61d6f3c5d1765cf7f358424a9e8411ab26b387685c38123e8f0bd
D2 SOFA-Plus-eFPGA 7576×107767576, 32328 5.7 MB634410b9d7576e7b5bcd64477c13cd721c84ff3e694392ee804213e260024e07
D3 caravel_user_project 7576×1077615152, 32328 3.0 MBc12667a873f455beb090c261ca051594a1ae36b9ade93cceea2477770c66a30e
D4 General_Purpose_Band 7576×1077622728, 32328 2.9 MBf430b3d372ed2199918074d25d4996fb195a5ebc39c6ce62753ea32c5aa9181f
D5 zero_to_asic 7576×1077630304, 32328 4.2 MB18ed4efc3bfe3e1a58a4b141dd95c2d1742ca26f36d43afda93f638d659318f0
D6 fast_gcd_for_large_i 7576×1077637880, 32328 13.3 MB509cf429cecc87ed491be9035482840c9135451d868f576a9dbdcc901050bb57
D7 Columbus 7976×1077645456, 32328 2.8 MBc04956a172bdfbd2abf702c0cca1e3780e90d9c12c0faa9f292852e147f8566f
E1 Space_shuttle 7576×107760, 43104 5.0 MBbedc0b182da7ded69c3b39850b2701df9b9e8d52604027ac7d8781e797754119
E2 subservient 7576×107767576, 43104 3.4 MB577c7a77bc98ffd6158748643bd8e6fa5d1658168bf1668fb166fdb02f5603af
E3 caravel_analog_fulgor 7576×1077615152, 43104 2.8 MBe9a2cba6f38f1a8939b1808087b9e06958c0fca19731a0e42a3a92c813dd8309
E4 bandgap_reference_de 7576×1077622728, 43104 2.9 MB6e7613037f2994b520b1a5b3835172e0e2d96a126f7e22ea92fff365516ce1a4
E5 renml 7576×1077630304, 43104 6.7 MBdc0fac9649bf2ca1ef53965835eb38cd11fd3456824372e2ca70dce409300c25
E6 io_expander 7576×1077637880, 43104 3.0 MBfd765c7c06034f5c55b44ac20e44230ab9640d0c9de8385b68d0feda10747613
E7 digital_pll 7976×1077645456, 43104 2.9 MB4f639079d7958ce7952303bf06907234d170a1f2dd5a0b4cb1685536a0bd2073
F1 zero_to_asic 7576×111760, 53880 4.2 MB60c2250f3d3456866a537ddff7e42a0f64eb5f21587e3b1de0239d00315d4bd7
F2 caravel_fpu 7576×111767576, 53880 3.5 MB172b74301c027a0c3f038aa7ef62e9199718813fdc3f392348cccef536bde494
F3 BrqRV_EB1 7576×1117615152, 53880 8.5 MB4d896cd7165e678cf3b0eb7c7d8945d80334fc6a12613b3526ca7d874e66db16
F4 hilas 7576×1117622728, 53880 2.8 MBc6ea83e19dac4bdd130d8993a950d02bbddc89c7b84080e77acd3b95fd254179
F5 vlsi-sky130-analog-c 7576×1117630304, 53880 2.8 MB7a2577492f780eb6d2d490e1fc20f3e231885c26c3e0cb6f726699d5213e3ba1
F6 sha1_engine 7576×1117637880, 53880 3.6 MB459fa0908b65be2998064b95da231e643cbb1a8ca27a374ceb6b798955c59a8c
F7 caravan_openfasoc 7976×1117645456, 53880 4.4 MBd2d67c4bae0cc55b5dde929adea11bcd0081b07d6eee57b8380fb2b6a2db1ab2

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 LICM1 on mpw-002

Resolved: reticle 5CS8007AC, run mpw-002, mask LICM1

Mask layer
LICM1 — Local Intr Cont.1
Process step
93 — Local interconnect contact mask
Drawn layer
66:44
Layer on the mask-layer GDS
43:0
Detail
LICM1 = licon1 sized (clicm1.3a/3b by spacing)
Also
Via 0 (???→M0)
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.