mpw-007 / LICM1 Local Intr Cont.1

the LICM1 shapes of all of mpw-007

40 of 40 dies rendered.

463,190,491 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 (214.4 MB in total, largest 11.5 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-007_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-007_LICM1_reticle.png
the stitched reticle, full resolution
173.4 MB 739f6f88c8235ee915c2e9632b99b134ba7f778fe9a383b723179e5cf6bd019a5ef93276 bd23547e67202f352e0aa8f78faa9c4b0c25df449050499ed4ea4d6af6f80f80
mpw-007_LICM1_reticle_overview.png
the same image scaled to fit 4096 px
2.3 MB 4cb0fbd64c8d608adaab6bf26badad78ec75dcfc1e4f40781b1883f7ff0f12f0ad1c090e 3491a3026378e3bf14455db99d901fbea97f6b74aac69ac85e354540c3c011fb
mpw-007_LICM1_tiles.json
where every tile belongs, and its checksum
13.6 kB 546ecbacfe956cbdc7032fe51ae2f56f273b7d5df9b2dd88c3d4c8cb2331c9be88ec4c51 252892071b0d4096a49dc5f50281ffc02b0c264439e9967a23f18e708594ad70
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 tinytapeout 7576×107760, 0 4.1 MBffdc119d14c25720a77b550fed81a475dfb6c04775988114235188ffa7b53c31
A2 zero_to_asic_course_group_submission_mpw7 7576×107767576, 0 5.5 MBc624fa2860de58a3977c89291404816ac74244847714857c9e1eccc907ceedda
A3 microwatt_mpw7 7576×1077615152, 0 8.1 MB68ec7da3b6a42d9e092f0268865e138b88aaed057ee917e447c5091a6fe8d904
A4 yonga-can_controller 7576×1077622728, 0 3.5 MBbb8ae5ebf9844082750aa65186598bc35ca383a28f90c946708a282eaf7cd9e7
A5 rocketalpha 7576×1077630304, 0 8.0 MB0239f17eb32e29cb59bc39e4c327d6351b3e4607517eee54136ea742aa54bf2b
A6 riscduino-dcore_d3_3 7576×1077637880, 0 8.7 MB2286d76d2e54b3f94aa8f2334ca5a15f9510f7a2c7f88fdc8e0ceedd86c926cd
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 riscduino-qcore_q2_3 7576×107760, 10776 8.7 MBde4485075a5bb244a620320b61bd9e7aecdae2e0beb734d8303b974c6098faf3
B2 riscduino-score-s4-3 7576×107767576, 10776 8.2 MB00247b3b309a63770c362cc0e225526eacb7a6a9799ea2ca8d6bc4af8649e765
B3 nanofabrication_project_using_openfasoc 7576×1077615152, 10776 2.9 MB86c5e0561766fe331304e22a342869fe81866b76e292c9ad4ed51c3320c17938
B4 sramtestvehicleg3 7576×1077622728, 10776 3.3 MB8f7654eb9928ddb6bb50f08bb06577087b59a54f8c7b635f40a785c1d7517396
B5 analog_frontend_for_particle_detection_resubm 7576×1077630304, 10776 3.3 MB529fafb1b09e58d1efe73922ad195fb75c2304635e64abb5714bf661c636d91b
B6 isa_16-bit_microprocessor 7576×1077637880, 10776 3.6 MB1b7ce52b622c9c34315718369af1e4ce5873fa9f5e7e2e7e418ab32b5db93471
B7 reram_crossbar 7976×1077645456, 10776 3.7 MBbb3f3c409478d2a605173c658834655c82fe3a33b8e4398c2fed19ea57813b0e
C1 trainable-nn 7576×107760, 21552 6.4 MBc5272004e97158b813b528ec0cf57c80cf94276784c7ba621f57e6ef467c4dc1
C2 10b_adc_and_analog_support_-_update 7576×107767576, 21552 3.3 MBafba1625403ddb181061e645152b21a24c2a7f02f48e634035a4add0da71f6a0
C3 bitcoin_mining_asics 7576×1077615152, 21552 3.8 MBa3e1c10e029c8a0fffcbe47a08e53a3af0e13e2ce3eccf6e00880cd801bdc259
C4 yonga-mcu 7576×1077622728, 21552 6.5 MBe5306402393f4444aeb262377483dba5baaab9ad80feac616276d420af9cd429
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 soomrv 7576×1077637880, 21552 11.5 MB3c90018ba1dfcfc51be4aee898c6d6857e0e46316fc2ba9b56eb8f740b750031
C7 marmot_risc-v_asic_for_motor_control 7976×1077645456, 21552 7.5 MB164c41de1c9f6ab87f045ad251e7946b543c63db577a4ffb5c178c83779dfae9
D1 mixed_signal_circuits-jun13 7576×107760, 32328 3.2 MB9dfc0ed8cae139cf685f6a29487875fa816e4acc00a0d87aab89fab787415632
D2 fpga_programming_management_unit 7576×107767576, 32328 5.6 MB183f045bed819e97a16c4135f0407dcf742f5cefe2c47f183e4b35256399631e
D3 warp-v 7576×1077615152, 32328 4.0 MB053aaeb5e813aea808b128b67fdf24144b966904a300d8473c7cbef86592cb3f
D4 leaf__mpw7_ 7576×1077622728, 32328 4.8 MB752455eb16efa579244940239d2758c1f03d8f5e44cf1d31bcae294ac2718e31
D5 in_memory_computing_sram 7576×1077630304, 32328 3.8 MB07711183f8803deac0fb1445e2e2d6b764ee8e2151ef868f7108039cd277b5c9
D6 rng_based_on_a_figaro_oscillator 7576×1077637880, 32328 3.5 MB8db77478effb8436fe24363b851af2e4ef92de960d5307aaefc85881a71f6ba9
D7 reram-controller-mpw7_v2 7976×1077645456, 32328 3.4 MBbd49380eb1839d6f95a6cbf96f21303c706dec90c8ef0391d4f67ad3c71f8e0c
E1 enhanced_chaotic_oscillator_design 7576×107760, 43104 3.6 MB85945847c34f86a9c923d485dbc485e657c9b9fb5f1399f009ce832518667f82
E2 in_memory_computing_rram 7576×107767576, 43104 3.9 MBfcd0aa234b107ab48725a00c9d0477565c82cf4f0a1b977b15bb7b3c24fd817a
E3 rram_imc_v2_flat 7576×1077615152, 43104 3.9 MBfcd0aa234b107ab48725a00c9d0477565c82cf4f0a1b977b15bb7b3c24fd817a
E4 topmetalse-dps 7576×1077622728, 43104 3.3 MBc28598841e09ce4e2fdf15ddaa5c51311dccb676b28546a01fe00d95aba12543
E5 chaos_automaton 7576×1077630304, 43104 10.7 MBc0fdb369851c19991a3732daa1dff36969a3326fca451ae1c19c04a7b917d044
E6 hehecore_resubmission 7576×1077637880, 43104 5.9 MB5bcd209f5013ac7ab35620ce8b7902cba9920edb57f49521eda6d1b2bd79f6be
E7 waveform_generator 7976×1077645456, 43104 4.0 MB6bb67c9c82820fd527eb35101537917879e9fffc259f71e96e57b8d09ad81e2c
F1 rift2core 7576×111760, 53880 4.1 MB82b230510d5afe79e52ac2bd560f0921a16421b3ef504f1a3af6981deffa8b52
F2 rift2go_2300 7576×111767576, 53880 10.7 MB82dfd707369b71bb3413c2c8b746152b44d79a4786f683c54a9953d1ff5ac7d7
F3 sloci_resubmission 7576×1117615152, 53880 3.3 MB611b4874c68d87589c793aa60a7ebaff0a0e0d631c14faf1f9575206403db453
F4 systolic_array_matrix_multiplier 7576×1117622728, 53880 3.5 MB3a8cc151be1315d42cef073af9181b3bdb482bdb69f90c1fcc09c33ec326a6ce
F5 crypto_aes128 7576×1117630304, 53880 5.3 MB7c9b6d929121cf6f181b99036f69eead4aa87f52613f8ef426880974e1cb767c
F6 graphics_controller 7576×1117637880, 53880 4.6 MB23b844a35848922df146e106ad34694da91ad8cf14aa9db0920624271232dd57
F7 prga-test 7976×1117645456, 53880 8.6 MB43a47e4fa237f5906e554eb4169d6a8b369d3e2bfd7590aa51d8d1d969470c26

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-007

Resolved: reticle 5CS8016AC, run mpw-007, 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-007 — SKY130 MPW-7

Reticle set
5CS8016AC
Run date
2022-07-08
Submissions closed
2022-09-12
Projects
106
Identification
inferred — Sequence after 5CS8014AC=MPW-6 (8018 is the re-made MPW-4 set); packing list 2026-08-25
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-7 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-007/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.