mpw-004 / LVTNM Low Vt Nch*

the LVTNM shapes of all of mpw-004

40 of 40 dies rendered.

135,843 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 (7.1 MB in total, largest 279.7 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-004_LVTNM_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-004_LVTNM_reticle.png
the stitched reticle, full resolution
5.1 MB e6a2a45b27d39a59dc9f5162457e045b8ee91134db715eb4b493b682b58682df35cd44b8 26f5de99de1cdf2084e1c56b9ca0ae146ce989e2bad4d64ebe452ba58e185dea
mpw-004_LVTNM_reticle_overview.png
the same image scaled to fit 4096 px
402.9 kB e5e6f183bcbc153b6ae1accc6112a41a544ba6eab90cf9dc2b92f082c23d0f901709dfe0 165b37c3696fcefd89947e71de83382b7518dd60ad9b39870ed886901ccdce2f
mpw-004_LVTNM_tiles.json
where every tile belongs, and its checksum
13.4 kB 7a76ff503a798b9b4cc7a21e7848fa98a075052789a627aee33adb0be991832def4ef825 9cb3cb258f80406fa67de387bfe7d9d97de4ec6c7c3c2c852cf232138b91c80e
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 zero_to_asic_course_group_submission_mpw4 7576×107760, 0 174.9 kB86740e8d90921611f2f630b0e9ca479a68c6b2826929e35c5aed5da9013a0a0f
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 168.5 kBba3a2d382d4b41db8ca7218e48ded27710ac4a263a5cadc2c3d2169b4c718ba4
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 156.0 kB2dbbe6da50eec43a7cb43a8dcbd37387ce5373b8d71f440f6c200cbf431bd2bb
A4 pifive-soc 7576×1077622728, 0 162.8 kBb7c0aa137d98360f16f3e38d0117426d4e8705072e6075b5ec3d46ea107e0f1d
A5 ram_generator 7576×1077630304, 0 166.8 kB9eb40435f410b7736b2077ad3ea33f85c411adf85e0d1712aa782845af1a2255
A6 space_controller 7576×1077637880, 0 160.7 kBc378a7c7429130da5f72a1e47c7bec89fb343daca01ea7e2e33036ee65626a9f
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 165.1 kB98eb8b790fa45e3b1d9cda8d7e08d32b2628f41f0c9d7b6d3d1b436d8175dded
B2 4t1r_testchip 7576×107767576, 10776 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
B3 yonga-turbo_encoder 7576×1077615152, 10776 161.8 kB10006198348dc1c2c026f5981045a84ed5cf221b511e2191fecbfff819ebf7c0
B4 icesoc 7576×1077622728, 10776 279.7 kB6a0cab1a79f51584103e1cb9edd2b17324dad99975ca0ea51728d5911aaffda9
B5 key_value_store 7576×1077630304, 10776 158.7 kBd7cd3bc875c0350eff474929a9378bf35b6761f8385a0c9f27d1b07309a8af73
B6 subservient-mpw4 7576×1077637880, 10776 162.0 kB315bf980123af894adcad09698228dee32a856ad4ca5bd6855b20a5844be387d
B7 logic_bist 7976×1077645456, 10776 201.3 kB5f3351e0aa10cd14f74ce0f1d1ec5ecbc3a74852e1c4713d0dc82d6d0df02921
C1 riscduino-r1 7576×107760, 21552 175.7 kB9108d3eaee5b5bfd82972298145d9afb4995385306a6f2f37dbffd19ae55cf5a
C2 template 7576×107767576, 21552 160.1 kBdfc2a52b5ef04e2bb73314068f4724b33e1e82c9e1f7431e39621072e12a2cc0
C3 vexriscv_soc 7576×1077615152, 21552 161.4 kB6d7bbc9722e9187e0bec2f0fed295b637899d97efe0ec1d904d70ddda6f05ea4
C4 ring_oscillator 7576×1077622728, 21552 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 153.0 kBd00f8c9be508aa3e73f987915c3064c70278d389e3e62191f477c6f76fc628c8
C7 approximate_multiplier 7976×1077645456, 21552 165.4 kB81e429491e119a901b1be1c5b4c0697e9a55a70f5a5bcfb356413b903c7c96c9
D1 icd_fast_nu_mpw4 7576×107760, 32328 154.8 kB6c23d70569fc0ded2b04dacb07ae69ea0a7ee3bed11840818f21e11bda6212df
D2 rram_testchip 7576×107767576, 32328 193.9 kB86e66fe52b5872d8d4cceff76473bdcac27c3df190e64cb87021b3279d0ad71f
D3 rest 7576×1077615152, 32328 189.9 kB47d66616ef77d6706961d04a8ea6ed144ba49e040ff077edf0d8cacdf2d23dbe
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 158.7 kB456e3aa5bf0da7083c821cab95c0667a66a5460918b242d8e89dcbc84f403826
D5 sky130_radtol_test_chip 7576×1077630304, 32328 188.6 kB39b3f584336ea60064c2682912533d8d1fda85769760baf03208951db6a5948d
D6 two_stage_cmos_opamp 7576×1077637880, 32328 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
D7 ks-guitar 7976×1077645456, 32328 169.5 kBb85ff933ac3af1599bdc6e628ceaea47f0f77720d6f584c20542ee908029829d
E1 ks-guitar-2s 7576×107760, 43104 168.6 kBc22cdf1286d936d364bd7fe154beba8326a565c2531681cafd4b66b2ddc5596a
E2 yifive_a2 7576×107767576, 43104 176.8 kBbfe097ac6f0623ab8641abc571dc6548297802e4fcf0c57db98211f8d9339418
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 157.6 kB333bb02986e4bb767cf3f90a050afae79c7776ae0172aae5dc4527db2c8c1cba
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 154.8 kB86e2c778c5ec6d1eb8f096d99a0c425eb08f43d133fbf0b633444a400de1f94b
E5 junga_soc_mpw4 7576×1077630304, 43104 161.4 kB6d7bbc9722e9187e0bec2f0fed295b637899d97efe0ec1d904d70ddda6f05ea4
E6 ibtida-ii 7576×1077637880, 43104 167.4 kB964f97a5c590ba5f90781420066a5de92728a56f5c03a8c41f1842ad4d3a067b
E7 azadi_ii 7976×1077645456, 43104 201.3 kB6d897b4b908fd5ee88876a01152b400445211ba737014245adcfaef432c2b929
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 277.5 kB581e4a0faad6ef8720b27c384d159dc6b0c81e4139984f4aaa4adf23c0e8982a
F2 current_starved_vco 7576×111767576, 53880 156.4 kB4a68a5ec77679ac34bd066f60228d85437988ca3a0d5f9a0a7c964eb07900ab9
F3 updown_counter__test_ 7576×1117615152, 53880 164.0 kB61eff74d4121767b6a25146c7f308945e3bf774563020956ae82c1168ba13ee7
F4 skullfet 7576×1117622728, 53880 156.4 kB4a68a5ec77679ac34bd066f60228d85437988ca3a0d5f9a0a7c964eb07900ab9
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 156.4 kB4a68a5ec77679ac34bd066f60228d85437988ca3a0d5f9a0a7c964eb07900ab9
F6 kasirga_k0 7576×1117637880, 53880 170.0 kBfde2f83179da3c4cdb56e056c979303eb12134cdf3039de756e8fda2b4dd1b55
F7 iotestvehicle 7976×1117645456, 53880 160.6 kB6a69ecd65dc386f538cb8789b6adfcc3082e8aaf4d4a868d4542e9e43fefcc2b

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 LVTNM on mpw-004

Resolved: reticle 5CS8010AC, run mpw-004, mask LVTNM

Mask layer
LVTNM — Low Vt Nch*
Process step
14 — Low Vt NOMOS mask
Drawn layer
125:44
Derived from drawn layers as
125:44 OR (64:20 AND (78:44 OR 81:2))
Layer on the mask-layer GDS
25:0
Detail
drawn lvtn plus a created part [nwell AND (hvtp OR areaid.ce)] OR (LV nwell over varactors); only the drawn part is rendered
Used in SKY130
yes

mpw-004 — SKY130 MPW-4 (original)

Foundry product
EF MPW#4 (+ 'With ReRAM' split lot)
Reticle set
5CS8010AC
Run date
2021-12-31
Submissions closed
2021-12-31
Projects
52
Fab lots
4216266
4216266
4216266
Identification
confirmed — Lot records: EF MPW#4, lot 4216266 = 'SKY130 MPW 4'; the set is absent from the 2026-08-25 return shipment (destroyed 2025-06) — see 5CS8018AC
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-4 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-004/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.