mpw-005 / LICM1 Local Intr Cont.1

the LICM1 shapes of all of mpw-005

40 of 40 dies rendered.

397,442,461 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 (159.2 MB in total, largest 8.2 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-005_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-005_LICM1_reticle.png
the stitched reticle, full resolution
94.3 MB be3ecb3a88b134c7516302df5c0c65710ed87f078b5501ca983e10fd72d6e1c7c5c1da5f 7ccc6e05235c5f6fba6915c7b605dbd79c03c4547fe9311313bb6460a044b3e7
mpw-005_LICM1_reticle_overview.png
the same image scaled to fit 4096 px
1.7 MB 0f613b187dc2fdc3dcfa0a2554dd48f6fae02b362d31a77a19eadd2589a674c4468f15c9 8464b028cc8a50e1ee2c405ff033e4b356a5cc5ad5fa445a8126abefa51ff949
mpw-005_LICM1_tiles.json
where every tile belongs, and its checksum
13.6 kB db43f0a81af9be0083c10c050c984ae949e4d3a6e39c4d0eb9b3ad35d1a57b74d2dd55c6 c36ae9205ae44c71309a0fd5d0e20fd7ef6d805235eed763cf701a422a13e2da
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 pll-based_capacitance-to-digital_converter_mpw4 7576×107760, 0 2.8 MBe989255aeaf5c1bf1adb14f2fbf0aaaf92e04eb0039ad67f0aecf367843db240
A2 mpw5_cache 7576×107767576, 0 3.1 MB0801ff1fe369e346909a38cf9f2b0c1e49a84a5af9477368aecc3afe71695f48
A3 zero_to_asic_course_group_submission_mpw5 7576×1077615152, 0 4.9 MB178c9c3e73aaa15fa43398e527c1ce6480a3d47ad1d5430bc061f69216a09a29
A4 zero_to_asic_mpw2_rerun_on_mpw5 7576×1077622728, 0 3.9 MB8f51f852d424adb1dff6a3754ce20da1b9e7221c78e0dcd004c46d4dc27d6e63
A5 zero_to_asic_mpw3_rerun_on_mpw5 7576×1077630304, 0 3.7 MB75904830f648ed12894940e9d6a6a99b925ab0864f84e3b709a65fc6b248bdaa
A6 zero_to_asic_mpw4-rerun 7576×1077637880, 0 4.6 MB69e7ad19f9edf3684011255504eb56bacac8941498b38f25030357fa8caa4019
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 actuatorcontroller 7576×107760, 10776 3.1 MBcdf2d7e73ba4b6c72bf71592c18de1a857d2d18944eb7a9edfce70d5d5fc2f0f
B2 microwatt_mpw5 7576×107767576, 10776 8.2 MB31bd4b1388d86a7c1b2ab5681d6d74d40e61141d3da23517473eac3d6e886670
B3 armleo_gpio_mpw5 7576×1077615152, 10776 3.5 MB1072a303273c968b50cb33cac2c0a5c3a8dbe72c83015958ae3e7de8de72d02e
B4 fabulous_efpga 7576×1077622728, 10776 7.0 MBe7d63c978a389a8a2e1baef8d7f9fc655122c913c1fd0ed45a6edbc03d073208
B5 i2c_controller 7576×1077630304, 10776 3.0 MBee1af82d68670f0e839ce801a410a0f3018aab13ff002b0ba9c59eec26e49f38
B6 lbist-mbist 7576×1077637880, 10776 4.3 MB4c446347de04d888405544a06f5bf3c12d20f03199d18fdf83a27ff961c18b40
B7 riscduino-dual_core__rd0_ 7976×1077645456, 10776 6.2 MB6134583f99a1c06e4efc94e4c3f384bba0023ddf174c2e419e7f16f706dbb5b7
C1 riscduino-qcore__q0_ 7576×107760, 21552 6.1 MBdb2a54ead1349574b842c5c8e057611043340d9e71ba1eed35ccd281217a5ad2
C2 high_speed_vco 7576×107767576, 21552 2.8 MBf2eb92b95fca497caba4e107038d60e6d6d43e4a087f75310d8e2008e4ba7db3
C3 openfasoc-cryo-gen 7576×1077615152, 21552 3.0 MBc4c7a3f1bb8e38bb5c36497d26631fc27a22ea42f56a71df7ac8af54fa7d5284
C4 microwave_signal_generator 7576×1077622728, 21552 2.9 MB90c0e7ba9dcb84d58d0a8498b46828129cb76450e66da1d9a217e2cf607ba8d9
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 pico_design_resubmission_mpw5 7576×1077637880, 21552 4.5 MB6c06168bc302373ee229c8b9380f5e4182cf5356a40639e7edd344e2d8bb6ec0
C7 ask_modulator_and_impedance_transformer 7976×1077645456, 21552 2.8 MB9da4e96e8b22850ef7964968a21cf5d2cdacc227f90c9b4e5f1c7286de564eea
D1 baseband_inductorless_automatic_gain_control 7576×107760, 32328 2.8 MBb5a90984b3b06eddee882632b4b8d6925dbc1a70fe236a3c9f217ab32bc50db7
D2 azadi_iii 7576×107767576, 32328 5.1 MB40f3b3a58adef23c0dc4b40b5ae7821b1a2c4762ecbc896630ffe9b208494f84
D3 tia_for_physic_experiments 7576×1077615152, 32328 2.8 MBac360e0c76b3ec9d175f6134652eff96155c4cd37a207398b2f1a59d51b6948b
D4 qf105 7576×1077622728, 32328 5.2 MB0cd86b19c0b65a6a16754b295332156eda17beb1c93596f9821deeb737b3980e
D5 coriolis_test_soc_-_mpw5_vexriscv 7576×1077630304, 32328 5.4 MB28d8e249ef31069f5b625b69c5b74ac5e44a98a5439f9b928c086a005274bf31
D6 junga_soc_mpw5 7576×1077637880, 32328 4.0 MB454c2a2466694ea247e544cdd14277baf7df28ee929fd21d784a7564affbafec
D7 nand_flash_mpw-5 7976×1077645456, 32328 2.9 MB226ce7a338ee43119bd2034b93c1c9ac8e476cd6d2069e0e9beeb1e1d9732ae2
E1 kasirga-c0-mpw-5 7576×107760, 43104 4.1 MBf0b727290f852be2747099f5f6c37458f42368311043fd1f1c97510c91c2a867
E2 delta-sigma_audio_dac__mpw5_ 7576×107767576, 43104 5.1 MB696dc8023a671a432d9a7572be2df24708e0d2f34244d2f7183054a4473c3f61
E3 wirelessenergyharvesting 7576×1077615152, 43104 2.8 MB77e6319cefaf661e563fc0759b2781bbf5019502da56523711e95419c8227100
E4 caravel_raster_engine 7576×1077622728, 43104 6.1 MB68ea296fbbcba9ce4f1dc42de99606f43db2a78694f5b4360c58cda574b6a274
E5 DDR3_SSTL_TEST 7576×1077630304, 43104 2.8 MBfd031fa9e20352558a93b1f0f0d4bea1d3864857289cfcf3ed54a361246a721d
E6 accelerated_risc-v_cpus 7576×1077637880, 43104 3.2 MB1326b6cac667bb574a6466d33eaf4e5094ac9539cf49277a49c88591e4580a84
E7 alu 7976×1077645456, 43104 3.0 MBa1d47e496b9b86a8100f2b70a80ddf22347b3d927e5afc83421734d75f18f604
F1 4ft4 7576×111760, 53880 3.7 MBf09aabc2ff9c83ae039db910be31f2d576736e85c48bc5eaefa7b7931a925d4a
F2 rng_chaos 7576×111767576, 53880 3.0 MB7bb01a5764a9c192c66a7191d99474be201d8d93d53be06645c1cd04a0bc4557
F3 uetrv-ecore 7576×1117615152, 53880 4.2 MBf1a046dcf056a582e3fbd98614ca325dbf168ec3cee7f6afb8ff78090ca805df
F4 systolic_array 7576×1117622728, 53880 3.2 MBbf95e0b5a693ba5ac65f2726bceb5836a7259825ae05bb30e8696e4eedd19409
F5 reram_test 7576×1117630304, 53880 2.8 MB3ade387d5cf1e2cd850b1bf14080f83c2dc1f3ab94f3d8b0f8d78173defa261f
F6 secure_memory 7576×1117637880, 53880 3.3 MB6847da851e241ba3b4d46ecf58985d2cba901e6305ddd0fbc684bb3c3ee8f1e4
F7 asynchronous_fibonacci_counter_testfix 7976×1117645456, 53880 3.1 MB3477e748391fe2d2a2876fd4acd74fb2749553067e1c5b20ad4c766b73f89501

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-005

Resolved: reticle 5CS8011AC, run mpw-005, 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-005 — SKY130 MPW-5

Foundry product
EF MPW#5 (+ 'With ReRAM' split lot)
Reticle set
5CS8011AC
Run date
2022-03-21
Submissions closed
2022-03-21
Projects
74
Fab lot
4229389
Identification
confirmed — Lot records: EF MPW#5, lot 4229389 = 'SKY130 MPW 5'
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-5 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-005/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.