mpw-003 / LVTNM Low Vt Nch*

the LVTNM shapes of all of mpw-003

40 of 40 dies rendered.

118,691 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 (6.7 MB in total, largest 189.6 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-003_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-003_LVTNM_reticle.png
the stitched reticle, full resolution
4.7 MB 9b50a0cd5b55d2eaf71e4469d09a68f1cb64f2427c58137ebb86741f95994e52b9f402ab c90a9c2bd059836d66941e6a0b5de5ec449d58484d1bd78cd381b6321a70be09
mpw-003_LVTNM_reticle_overview.png
the same image scaled to fit 4096 px
322.8 kB a87e753b9842d71c2113ce4899dd4b26ff87606fffa6a885f640216a0b05ab460cdbbf09 3cddf8c54f641e04816e86310a6640390059567eeec34681d66d25cb557fefc1
mpw-003_LVTNM_tiles.json
where every tile belongs, and its checksum
13.5 kB cb6ae08fa66e6b44705ba7129d5c02c1bf89cda16676cb120f3993075ff4d8dc27adab3f 3458592285bf002cffe0b957f7e04353e35f377ace062995eab87675015e61eb
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 stdcelllib 7576×107760, 0 160.1 kBdfc2a52b5ef04e2bb73314068f4724b33e1e82c9e1f7431e39621072e12a2cc0
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
A3 openram_test 7576×1077615152, 0 161.0 kB4b9d546334e5de723f60e881d849acb24529c2e52aad38910e4786f011902402
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 170.6 kBb6b021bde273cbd23e8a38a144ec54ea3c5c8c306fac4efd891320dee9ed560b
A5 crypto_accelerator_v2 7576×1077630304, 0 163.1 kB41e81d801691780c58d96e6122443d41951dfd9f00146d9865b036c983232606
A6 picorf0 7576×1077637880, 0 161.7 kB933a015239ed1707e7c05c7ebff881bf6ed1256ea42788c10e16eec028ff62da
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 162.5 kBc54c2d36843de291b9aa1376a2514908fe00dad3b348db192a3365ac5a2c4ddb
B2 yonga-100m_ethernet 7576×107767576, 10776 161.3 kBe40a787d50fa5829e7c9cfc835247c490dec86e2e031b3911c5b7a7ef96845f5
B3 approximate_multiplier 7576×1077615152, 10776 160.1 kBdfc2a52b5ef04e2bb73314068f4724b33e1e82c9e1f7431e39621072e12a2cc0
B4 vsd 7576×1077622728, 10776 157.6 kB333bb02986e4bb767cf3f90a050afae79c7776ae0172aae5dc4527db2c8c1cba
B5 asic_key_value_store 7576×1077630304, 10776 160.1 kBdfc2a52b5ef04e2bb73314068f4724b33e1e82c9e1f7431e39621072e12a2cc0
B6 mbist_controller 7576×1077637880, 10776 177.7 kBb0d7872e7359fb40c291c28ec2e6810c481150fea8c5fc3059f950b3a6675588
B7 riscduino 7976×1077645456, 10776 179.5 kBa95fed337e11c2cbcedeffa65db43adbb0069fb080927c55985aa2c3deeaaf7d
C1 caravel_peripheral_extender 7576×107760, 21552 161.3 kBdac55537221c596a8561734e341d21807d505c19d5bed8b7b7c0a0be4e1e42bf
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 189.6 kB9f13033e5fc187d9d93f43c2898039259708d082a2ad9071b382212f1aec5c0b
C3 class-d_audio_amplifier 7576×1077615152, 21552 164.1 kB406a2dc4545a2021e2967147b97e65e136dd713810cc0541be5eafa639c10645
C4 efabless_processor 7576×1077622728, 21552 160.1 kBdfc2a52b5ef04e2bb73314068f4724b33e1e82c9e1f7431e39621072e12a2cc0
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 158.4 kB1901398a4815cacf13e9dcae98de64a11899f97d428f6cb1b67152192d05241d
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 156.7 kB38a6aed7c2e1c4f4fadc0a9ed5d8d0771e4114b5e3a432aaf42c0395b34e465f
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
D3 sziklai_pair_amplifier 7576×1077615152, 32328 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 163.0 kB6133084535e628d4e74c90bda399e8884f68f58534481652babae815c438c4db
D6 rotfpga 7576×1077637880, 32328 161.5 kB6c7e7cbb26a06590421223b03f32b8a705fbf5743e18e83f04c2d3aa63bb1745
D7 treepram 7976×1077645456, 32328 169.8 kBbd9ef8873eacacaae7c51a20dcaf7de736fcb93883558bdddf6388812770e5d3
E1 treepram-red 7576×107760, 43104 168.3 kB702951eff886361115b68f7c38822002a2222fe77e4c9b29ba07f8bd493e8b73
E2 caravel_jacaranda-8 7576×107767576, 43104 161.6 kB22239d61a5bcb6114dc5db9151dacc84e99953b2dfa06804a9d03dea3c6ed90f
E3 sudoku_accelerator 7576×1077615152, 43104 161.7 kB8ddd3be83d166fcfe76511d53afac249ec62f2a0bba253b9ea86c6880f22c281
E4 fixed2float_converter 7576×1077622728, 43104 160.1 kBdfc2a52b5ef04e2bb73314068f4724b33e1e82c9e1f7431e39621072e12a2cc0
E5 high_speed_adder 7576×1077630304, 43104 158.5 kB73f030dc00fbd2a4865875c175d2c35dcb406a53747398f365951188dea935b8
E6 my_proj 7576×1077637880, 43104 160.1 kBdfc2a52b5ef04e2bb73314068f4724b33e1e82c9e1f7431e39621072e12a2cc0
E7 pwm_test 7976×1077645456, 43104 164.0 kBfc716cead2d650ffd791367d7c7bbd80e697e0702b7ac0d2cc7256cbbb9f5e57
F1 elpis-light-mpw3 7576×111760, 53880 174.0 kBaafd610924aea31a6edc464a61585f12078b94d43015d5de4c01cb4a20efec71
F2 vsdbabysoc 7576×111767576, 53880 165.3 kB68e124ccc29fe04972ac158d37b2e304f324ddf1c4f450e026626bc33bb4784b
F3 vsdmemsoc 7576×1117615152, 53880 167.3 kBb06d8dc8c2598f6c927716eb0a18ecc617a9025cb9dc36d4bf48de4215abb0b8
F4 caravel_sram_test 7576×1117622728, 53880 162.8 kB9867c8bd16686a4e389a063e60022399b9406f23ab685ba531be6e366be9b2e0
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 157.0 kB5e0d38f9947219a73989c92e53493e087b01bb0fa98b6480a7f36f9909f89abb
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 164.9 kB9cba97a1abd62ab21032cadc5729e7141303b5c06d461694b810959ff5b3a433
F7 caravel 7976×1117645456, 53880 168.0 kBfc2eca19c59552bf8d8d9c00dabd0d7ea228b45dca17824192208b16bd953d9e

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-003

Resolved: reticle 5CS8008AC, run mpw-003, 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-003 — SKY130 MPW-3

Foundry product
EF MPW#3
Reticle set
5CS8008AC
Run date
2021-11-15
Submissions closed
2021-11-15
Projects
53
Fab lot
4206521
Identification
confirmed — Lot records: EF MPW#3, lot 4206521 = 'SKY130 MPW 3'; confirmed by a photo of the MPW-3 mask set's VIM2 plate label (DEVICE 5CS8008A-A, LAYER VIM2 560A 03-01, archived 2022-05-13), seen 2026-08-28
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-3 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-003/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.