mpw-008 / LVOM Low Voltage Oxide

the LVOM shapes of all of mpw-008

40 of 40 dies rendered.

2,256,706 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 (5.6 MB in total, largest 160.0 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-008_LVOM_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_LVOM_reticle.png
the stitched reticle, full resolution
4.1 MB 95c85dae1bbfbf6ce71ba63561137740ffd69fb528b87b86d1ecc42c6b2c72cb8503659e af12fd38916020027c8b2ec256d8013778f898fa69bc799691301b1c877bddf1
mpw-008_LVOM_reticle_overview.png
the same image scaled to fit 4096 px
234.8 kB 8e0f87ef877fc7c58955e5cae86844d804ce0890b60e2f4a4b3f2ff1fa7f00344d72f58f 2b53fbe34a2da478195f996c6d5c9a1b3dd5198c71db83a7e7c506a4d62f777d
mpw-008_LVOM_tiles.json
where every tile belongs, and its checksum
13.5 kB dcb89779c4509b5d9333bf876d4c3f5d1c361de78af849e89c748abe3bfd920cf2892478 1f5be383edca21f7badbaebd2113fa5f7b53c7725a5c3614040eefe94b851d65
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, 0 132.6 kB20e21178538ae098b9038ef87bb0e337c03305ba83b27a38b3f982afec902ce3
A2 iit_indore_mm 7576×107767576, 0 132.2 kB12a0906f95d21b782392b745f9f6846ab3e8297adbb9de67171cae2251bd3884
A3 energy_efficient_sum-of-products_circuit 7576×1077615152, 0 132.2 kB5c8c7325daa074ba35c7937e7910fc7f5f8888865789c6bb1d0b5c06534ebd27
A4 riscduino-dcore_d4_ 7576×1077622728, 0 132.9 kB7f2d73d83538256ccd094a61640ff2d9d1bc6decb3d60e56a12647488480bc5e
A5 riscduino-qcore_q3_ 7576×1077630304, 0 132.9 kBcef25dbe51bc4347aed1a6c05f4f887ee09a6f9c6c5329311f0a0753506b73eb
A6 caravel_mpw8 7576×1077637880, 0 132.6 kB20e21178538ae098b9038ef87bb0e337c03305ba83b27a38b3f982afec902ce3
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 nanofabrication_project_using_openfasoc_mpw8 7576×107760, 10776 129.2 kB80dfc3bfcc823b9f9c04e30c03430569dc842f9ad8a64ca048ecacac1d8475aa
B2 sramtestvehicleg4 7576×107767576, 10776 128.4 kB2b9ee6b4861bf1cc6b776cfd978c77fbcf23c7ff3091aa454f4b27f591f03580
B3 reram_crossbar_rerun 7576×1077615152, 10776 160.0 kB288c0a43561394d99f47cd19bfa3107494529e61da33f529507a719d603bc4f0
B4 tinytapeout_skullart 7576×1077622728, 10776 132.6 kB20e21178538ae098b9038ef87bb0e337c03305ba83b27a38b3f982afec902ce3
B5 soomrv__mpw-8_ 7576×1077630304, 10776 132.6 kBf0384be1584492ed578d500e3a2cabb9d34dd93ad58e625a48fe03ea5615156c
B6 clock_divide_selector 7576×1077637880, 10776 132.6 kB8c9505d01a14e79d4f166bf27d9578f7a53001d9d75882b1d70c7d5949a3c667
B7 reram_module_mpw8 7976×1077645456, 10776 138.3 kB5cbad85eef4dd8119b268a91fff56f9eb68ca8e6f1dd42aa80204e5f05035a58
C1 shapingthewaves_8 7576×107760, 21552 132.6 kB20e21178538ae098b9038ef87bb0e337c03305ba83b27a38b3f982afec902ce3
C2 leosoc 7576×107767576, 21552 132.2 kB5c8c7325daa074ba35c7937e7910fc7f5f8888865789c6bb1d0b5c06534ebd27
C3 decrypt_aes128 7576×1077615152, 21552 132.6 kBcc48ae76acc1a2abe1835152e3e01a038abdf1fb884f4abac99699582a04a713
C4 approximate_adder_axha 7576×1077622728, 21552 132.6 kB20e21178538ae098b9038ef87bb0e337c03305ba83b27a38b3f982afec902ce3
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 riscduino-pxt1 7576×1077637880, 21552 132.6 kB8c9505d01a14e79d4f166bf27d9578f7a53001d9d75882b1d70c7d5949a3c667
C7 fitbit_project_using_openfasoc 7976×1077645456, 21552 132.3 kB6218b3614d95e17af0d90533368255b9cd60911bd0fbb721e9e3bb93b808be60
D1 rift2go_2320_sky130_mpw8 7576×107760, 32328 132.2 kB84d3e4c13daf38687988ee2da71839e5af7ad2a79cecda8d02539723bbdbcacb
D2 hyperram_controller_for_sky130 7576×107767576, 32328 132.6 kB20e21178538ae098b9038ef87bb0e337c03305ba83b27a38b3f982afec902ce3
D3 hardened_alu 7576×1077615152, 32328 132.6 kB8c9505d01a14e79d4f166bf27d9578f7a53001d9d75882b1d70c7d5949a3c667
D4 an_open_source_hitachi_sh2_for_motor_control_apps 7576×1077622728, 32328 132.2 kBba29d33c15a9ca675f65df44bb8bee126d9fe4495ab8b72762e5d88d0098f083
D5 mixed_signal_circuits_mpw8_dec14 7576×1077630304, 32328 128.7 kB07112ec3e02335182132abdf5f1cccb7f9e4a1398abdc0b9ce858082120d1bca
D6 gf180_vs_sky130 7576×1077637880, 32328 132.6 kB20e21178538ae098b9038ef87bb0e337c03305ba83b27a38b3f982afec902ce3
D7 iiitb_tlc_mpw8 7976×1077645456, 32328 136.3 kB39e6da538b66c3828eda6eeb89b657f5f4180c1154399a4b119fdba7cd79505d
E1 iiitb_sd_mpw8 7576×107760, 43104 132.6 kBf0384be1584492ed578d500e3a2cabb9d34dd93ad58e625a48fe03ea5615156c
E2 iiitb_sfifo 7576×107767576, 43104 132.6 kBcc48ae76acc1a2abe1835152e3e01a038abdf1fb884f4abac99699582a04a713
E3 iiitb_alu 7576×1077615152, 43104 132.6 kB20e21178538ae098b9038ef87bb0e337c03305ba83b27a38b3f982afec902ce3
E4 ppcpu2 7576×1077622728, 43104 132.6 kB20e21178538ae098b9038ef87bb0e337c03305ba83b27a38b3f982afec902ce3
E5 mega4_reram 7576×1077630304, 43104 129.6 kBeeb7bda513e5c52cf5db3b941e1e71a2c4a2ed74b17792bd533246f62de14e95
E6 tiny_user_project_vgaclock_mpw8 7576×1077637880, 43104 132.6 kB20e21178538ae098b9038ef87bb0e337c03305ba83b27a38b3f982afec902ce3
E7 sky130cla 7976×1077645456, 43104 136.1 kB0a8158b780244ed56798609bb89f8d80f9c585e96f1b79c4c8dbf9c5e64976ee
F1 uetrv_esoc_v2 7576×111760, 53880 136.1 kBde57ef5c338b45f734bba8440179e8ed3c33995cf865f7f8d2c86ca5cc101a38
F2 sequencedetection1010 7576×111767576, 53880 136.5 kB49748b333de114b81f993aea3bd08a45bfdc7c14475cfc5d5a6a6365bd2599cd
F3 testasynctrimux-mpw8 7576×1117615152, 53880 136.5 kB1d013b00da607e55879f01ddaf34b7bcfb191373042fce331e04c97c4dbe472a
F4 iit_indore_dadda_multiplier_mpw8 7576×1117622728, 53880 136.1 kBb512e1f1ae44953535de6acc5b87628aff2d94e5760664038dde3eaa7c082d93
F5 modified_baugh_wooley_multiplier 7576×1117630304, 53880 136.1 kB0124abb2a2453b63c667b7a4fc79fe201d3b8ff9f04ab6a98bb8e68b6c877c04
F6 arbiter_puf 7576×1117637880, 53880 136.5 kB1d013b00da607e55879f01ddaf34b7bcfb191373042fce331e04c97c4dbe472a
F7 unigate-sky 7976×1117645456, 53880 140.3 kBff52a9654847b1bdcd5ae10c79a939dc0b1edc7adaa270e8ef82deaf68c1cc10

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 LVOM on mpw-008

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

Mask layer
LVOM — Low Voltage Oxide
Process step
44 — Low voltage oxide mask
Drawn layers
75:20, 80:20
Layer on the mask-layer GDS
46:0
Detail
LVOM = hvi OR tunm and the SKY130 layer sheet
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.