mpw-008 / FOM Field Oxide

the FOM shapes of all of mpw-008

40 of 40 dies rendered.

91,778,191 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 (208.0 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-008_FOM_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_FOM_reticle.png
the stitched reticle, full resolution
156.3 MB 2d521b192aed18214cb53520db8388090f13c2ee6e3c8f382ae35a3c6be499082c61f005 4dd2630bbcd5bedd90d28974054fdea0429ae8f345dc3dbf130a5da86d09b8cb
mpw-008_FOM_reticle_overview.png
the same image scaled to fit 4096 px
8.1 MB 960c3805e291caa97d9503f3dbf9b3ca6d53677a383f713cc7ecc11cfc281ea6d25e3c09 603f99fe2fda8b9820f507fcaa8a4e35619a3e7001c686c7430e12b59b49e8f6
mpw-008_FOM_tiles.json
where every tile belongs, and its checksum
13.5 kB ba039f4b3c1d0f1dc178ac6356302eb4970a25489a311e8e6ba346ae3c081cbf8831e4dc f758a214f3e7d4b40f6d1072f41c7aad93825332965efcc13bb1dce40f9e2091
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 5.2 MBafa07cbb0807b66d7777a40bdf869e32e61e0c36a9f5b465ecf2d7e789e911f1
A2 iit_indore_mm 7576×107767576, 0 3.8 MB41ca8a4d9f5b797d4065a22e302c889ab662546b32c2b4ff7a43c180bd7d8998
A3 energy_efficient_sum-of-products_circuit 7576×1077615152, 0 3.8 MBf0a2d353085285f52aa723f7ffbf6abb3062a165252a8b320b21d38c8332a053
A4 riscduino-dcore_d4_ 7576×1077622728, 0 9.6 MB76a56561da9fd86dbb453741cd459a6f4cde71f52b687825af9459732b417b97
A5 riscduino-qcore_q3_ 7576×1077630304, 0 10.0 MBa81a379be7c002a733465880ecc5c978aadfb3c432502bda81879a2d0fc6cbf7
A6 caravel_mpw8 7576×1077637880, 0 3.8 MB3b1ffa871bee752234887b9ee11345b4eb44a72c8c1b9d8842fdcb6ac8a25e67
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 nanofabrication_project_using_openfasoc_mpw8 7576×107760, 10776 3.8 MBccabca31fe72980da5b1c74b32adc7e4d063a775c91d66074afece22a6c7d057
B2 sramtestvehicleg4 7576×107767576, 10776 3.7 MBe9acb34a80c83b2504efef2ca8c09ba7193785fadde8e550222574b4425e3807
B3 reram_crossbar_rerun 7576×1077615152, 10776 3.8 MB5423341d2e29b8d002a770dc0b5f94cada84a66ba3c1f15bd9fce39e49f1da3a
B4 tinytapeout_skullart 7576×1077622728, 10776 6.1 MB4de72a8d027f880639de081e9bace41b87e45eef6a7d3abb78ac23ac019db47b
B5 soomrv__mpw-8_ 7576×1077630304, 10776 13.3 MB7f4fd875dd639f377dbbd5d21a795535990612b6b6d75e79ec53869be2acc148
B6 clock_divide_selector 7576×1077637880, 10776 3.6 MBcf171b218868cc88615e25bd4453d7aa919119df436ff30e0258f2ea91e203be
B7 reram_module_mpw8 7976×1077645456, 10776 3.6 MB83d0236eeb89dcf148c7f9a833dd5baa877f3f3c9023c85dcc98cfa0f62a2c71
C1 shapingthewaves_8 7576×107760, 21552 7.3 MBbff8bb6c4667cf0d44d0c27c8be03a4984fc369acc13b66d27562f5576d16f1f
C2 leosoc 7576×107767576, 21552 6.1 MBfa24a392e06d6099faae10a0b109110a87156c2c52bec0e36d78d5d16b01b495
C3 decrypt_aes128 7576×1077615152, 21552 5.8 MBe3f30776da88b981b186471095918b8b8bdb65a54e0cda17600851ba9bae53c9
C4 approximate_adder_axha 7576×1077622728, 21552 3.7 MB50eda9bd7760fda0da363659b81f3fe35a6daf399db5da5c0a7ce670c2edfd92
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 riscduino-pxt1 7576×1077637880, 21552 5.8 MBe074c6cef6b77a373ce2896dc473facaf6790f3f4ee6c63ee7dc5091b2230af0
C7 fitbit_project_using_openfasoc 7976×1077645456, 21552 3.6 MBd9bcf665c2172ed4ba6328736d528dce78114ce168a6b2f04179c6dbdb74c3a8
D1 rift2go_2320_sky130_mpw8 7576×107760, 32328 13.0 MBf5cd21f344828262e517fc28f1844b464608d5e3048f4e75b65d1db22904b4b4
D2 hyperram_controller_for_sky130 7576×107767576, 32328 3.7 MB03cfebdb90020c145366f546ef0fd68dae6773b3c6571f349f51f2ad07a8df76
D3 hardened_alu 7576×1077615152, 32328 3.9 MBddfb1964fd4ded3b7adeed074f68d3b3bc4bd746fb04259bf1dbe6622cc1ac4a
D4 an_open_source_hitachi_sh2_for_motor_control_apps 7576×1077622728, 32328 6.7 MBe274661ded7849245a93519f3729fdead3d4065d1b5a46fcb9a6f5da3331e892
D5 mixed_signal_circuits_mpw8_dec14 7576×1077630304, 32328 3.5 MB176154b7cee5b9e4cfdbd943ebd30e4532080fe7306a58542c03a3d3ae4c9d2e
D6 gf180_vs_sky130 7576×1077637880, 32328 5.5 MBa19bdc52d81673983ab6f41ffb40f4b5d8a41d7c4447910544ca2dda6a474c1f
D7 iiitb_tlc_mpw8 7976×1077645456, 32328 3.8 MBf5211cfd3928ff918a62e9d512c5bd600673d9550ff4cbf0f008ca1843b83cef
E1 iiitb_sd_mpw8 7576×107760, 43104 3.8 MB77a60804720b55afa8730332a14db8017b20c02be83dfb238f4dc5fc3efbda68
E2 iiitb_sfifo 7576×107767576, 43104 3.8 MBe1d474db5230808812f8b541d63dc2e4dea9ecd35155126908ec0f1fa4066870
E3 iiitb_alu 7576×1077615152, 43104 3.8 MB88f244ae8b514e04f044e48211a16e3c277ab47635e195fdab1b954c31bd3e94
E4 ppcpu2 7576×1077622728, 43104 9.5 MBed13fe4ad103c21e8f203d58fc67808e7b787300d7c67696d86ce3909fcd6a05
E5 mega4_reram 7576×1077630304, 43104 3.9 MB0ddb690b2883d24de29a790080c0ddc18f8f7f7e9880e4788e7539062594b44d
E6 tiny_user_project_vgaclock_mpw8 7576×1077637880, 43104 3.7 MBe877532f92c345560583bb12e6cf173b29be7331a2a05ae272c9608638f034fd
E7 sky130cla 7976×1077645456, 43104 3.7 MB35f9583ad739ad397e3baa7f419d5765515167fc971902fcae1e8ba190615f8c
F1 uetrv_esoc_v2 7576×111760, 53880 5.2 MBba51f1bd5d04e576f6a9141ea0263253cb20ee52076f5f4a294db882776ff315
F2 sequencedetection1010 7576×111767576, 53880 3.7 MBd86dd7ce6499924c6c4f4fc7f2bcd52bec778aaf227a65a8abcc6eec7148ffc6
F3 testasynctrimux-mpw8 7576×1117615152, 53880 3.6 MB573d4c416904f055c568fb0e904cdae5493972fe76e4a0974e4fdadc7ef85f32
F4 iit_indore_dadda_multiplier_mpw8 7576×1117622728, 53880 3.7 MB24089b6bd676bb605503ad66d3bed8db1e5c28793370c8766f805a859c234117
F5 modified_baugh_wooley_multiplier 7576×1117630304, 53880 3.8 MBe33b0fd40eeeebbc033f6327521e6cb8df0f6f0975d3e1adca495ae0f3bb836c
F6 arbiter_puf 7576×1117637880, 53880 3.7 MB9e9317d539ab947070a66955b07e282835af55a7b6f174318de7c42412073885
F7 unigate-sky 7976×1117645456, 53880 5.5 MB4f6125aa5b8cfa3a37ff4156cefe9810899a57a2e1f696a2a2d61ac1e9dc5403

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 FOM on mpw-008

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

Mask layer
FOM — Field Oxide
Process step
4 — Field oxide mask
Drawn layers
65:20, 65:44
Layer on the mask-layer GDS
23:0
Fill layer
23:28
Detail
FOM = diff OR tap (OR grown pnp emitter)
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.