mpw-002 / LVTNM Low Vt Nch*

the LVTNM shapes of all of mpw-002

40 of 40 dies rendered.

146,688 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 (7.4 MB in total, largest 435.6 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-002_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-002_LVTNM_reticle.png
the stitched reticle, full resolution
5.4 MB f26dfa5d2cea10ad70b7b7a24a30b165fbff0a189fd0e2a4177b79e1708dfbbd0b5c0d51 878bbcde058ee9e8be5e3de4d5371ea17e40288c87043a8436757006c6fefdef
mpw-002_LVTNM_reticle_overview.png
the same image scaled to fit 4096 px
431.7 kB 783f4cd97746b448bce750dc543878a37b065c197605ea71971493f0e7722a90c3308d4e 8a4d7e7e13b10c3df8f7cc710baea682ff1955f43e78d0a9aac46e1f2f8e3d4f
mpw-002_LVTNM_tiles.json
where every tile belongs, and its checksum
13.3 kB 9660c3f377a4dcf547f26415c4375b17ad0524b2c8f71a876ca21ea5375e373f22eb2fd0 3d66357918c733e3e568414ed3771319bbf911e72f68ae74a48e927e777371a6
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 axi_dma_using_spinal 7576×107760, 0 163.3 kBa4a61ab051daa518de35a2297308ce152e01bb3a78a8b68360e3fd195d8d372c
A2 wishbone_can 7576×107767576, 0 165.0 kB14be74f81765aef4dc4a5ade4961824752fba69ef032c5f1758ef77848c4b751
A3 Analog-Neural-Network 7576×1077615152, 0 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
A4 caravel_dsp2 7576×1077622728, 0 161.3 kB9f860fc953cf50f58952608c27c67a7833dfcc84f85f3f4b40cf330632740def
A5 eFPGA_v3_caravel 7576×1077630304, 0 292.9 kB054a92579ad95820a07eb66da037eda90c8342252590eba43cea7eac7097f22b
A6 opencryo_testchip 7576×1077637880, 0 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 yiFive 7576×107760, 10776 175.1 kB21db1d09637d245ac8063520e8569edc815bb33431a052b123790a7703f016c6
B2 lexicon 7576×107767576, 10776 169.2 kBdd58e006d4a34e4369ba3dca78a3a9551934759cd7c80cd22fd44bac8aa02a42
B3 ucsc_openram_test_chip_v2 7576×1077615152, 10776 189.6 kB9f13033e5fc187d9d93f43c2898039259708d082a2ad9071b382212f1aec5c0b
B4 yonga-lz4_decoder 7576×1077622728, 10776 161.6 kB7b7bdb565e533cf24976ef8b9e2738dc747553f9a3598a4e75a53ef30f94ab9b
B5 Potentiometric_Digit 7576×1077630304, 10776 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
B6 fuserisc_ver2 7576×1077637880, 10776 278.9 kB83c05a2e53830a499949fa08f5acf2ae60409bad454e6d169c5e7831fc57641a
B7 amsat_txrx_ic_mpw2 7976×1077645456, 10776 165.0 kB004511c47e7b2002b66e440435d5a762bfc3eeebb7a5675e9546bfa194a09820
C1 Comparator_3v3 7576×107760, 21552 152.5 kB3746a75bcca7ae3cca010ecafb5ddde584b3326d981fc0f8676547bb9b757a0a
C2 caravel_multi_encode 7576×107767576, 21552 162.2 kBef7a05cf0d5db074352ccf13320d84403e57dffe74c7ae36a41b41dd0f75781f
C3 kasirgalabs_uart 7576×1077615152, 21552 160.2 kB7b566c07a0d68cb13121223cec1a06e85b5ef0016cf5c0041743d46eaf199808
C4 Automatically_genera 7576×1077622728, 21552 184.8 kBe77adae3908e39524a283b9c645ee69c7f1f12a2152def8f448a63a0b0741a72
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 uqab 7576×1077637880, 21552 195.2 kBcbe0ea9721a6278c171f1d0a357064dcf9cc4b19346e2ede950c7aaac7e861d4
C7 caravel_azadi_soc 7976×1077645456, 21552 182.6 kB3d10e761d6ffe8fe52c7aa7327e79194cc3f092abd8cdcb44d0870152f02a673
D1 caravel_dsc 7576×107760, 32328 161.6 kB09427236d8cc2251965b5c1ca75e8622d933b43fe23886f58bc96462b1cb6de0
D2 SOFA-Plus-eFPGA 7576×107767576, 32328 435.6 kB75a08d3d8d8f1ebf580aeb4446104140e4297587317656c9c177c8d9e39d2b42
D3 caravel_user_project 7576×1077615152, 32328 160.2 kB7b566c07a0d68cb13121223cec1a06e85b5ef0016cf5c0041743d46eaf199808
D4 General_Purpose_Band 7576×1077622728, 32328 157.6 kB333bb02986e4bb767cf3f90a050afae79c7776ae0172aae5dc4527db2c8c1cba
D5 zero_to_asic 7576×1077630304, 32328 171.6 kB347e6c6e641fcbc02b46f35b3f727b3c7976834c8f8a7a046c57095411ac255b
D6 fast_gcd_for_large_i 7576×1077637880, 32328 168.9 kBb73761afffff593acecace94373d830d3d38fa0f42d6b3110c816fa1f3fbc4e8
D7 Columbus 7976×1077645456, 32328 156.6 kB5ffb5cc5579369d8afdf37f685c8ec4b01a13b554994ab0d045d668c47e89c40
E1 Space_shuttle 7576×107760, 43104 164.4 kB1b1906838891f942de48c60dbd5c3a1a56aadbc52ab5dfa0469d9b14e90dfc55
E2 subservient 7576×107767576, 43104 160.5 kB45fddce943aeec52d7a629220f8fa27d6d193a6ba8ad434814aa688f59aa5601
E3 caravel_analog_fulgor 7576×1077615152, 43104 153.8 kBd714617f474b8a7eff12024e082fe8690defa1d34ac267f5f42e88bc912f0c62
E4 bandgap_reference_de 7576×1077622728, 43104 157.6 kB333bb02986e4bb767cf3f90a050afae79c7776ae0172aae5dc4527db2c8c1cba
E5 renml 7576×1077630304, 43104 184.4 kB12e4a4fb5b0bf5d2391495d29768cf1d9dce6d4e5878337679b36bcf2b025202
E6 io_expander 7576×1077637880, 43104 158.4 kB58312c380fc61025af414318c9500d071d8f9d59c44e30b3c636111cbcd62d28
E7 digital_pll 7976×1077645456, 43104 159.1 kB605b45c37de86d9bcd2f68461878158917d6822e2ec9959984f50bd0da85b64e
F1 zero_to_asic 7576×111760, 53880 175.5 kB0e7cc0357afc217d96135528cb334f375b2295e68fc692e96442087e9002929d
F2 caravel_fpu 7576×111767576, 53880 164.0 kBd9cc1ea3108aa5e993ee66e1ebc1558cf7e98f1cdf2d05bfb1deb8b43c9cef3a
F3 BrqRV_EB1 7576×1117615152, 53880 199.7 kBb5a6fac7143ba4f05a9a1464966637f309304d63d1d0ced4be5c1c8a80a394da
F4 hilas 7576×1117622728, 53880 157.1 kB670d8e52bc1c83bd4dcf01bf7545502a4bf1ae8a0072a3e6e9414e330187c8cc
F5 vlsi-sky130-analog-c 7576×1117630304, 53880 156.4 kB4a68a5ec77679ac34bd066f60228d85437988ca3a0d5f9a0a7c964eb07900ab9
F6 sha1_engine 7576×1117637880, 53880 165.3 kB46be902fbe6b196c1d78614b7f1b6a2effd57fcd0db03239267f2fed88144d43
F7 caravan_openfasoc 7976×1117645456, 53880 190.2 kB5eb17e32a0c384728ce31a233e316fadf1e4bef01f8ad506ba13be92ea29824b

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-002

Resolved: reticle 5CS8007AC, run mpw-002, 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-002 — SKY130 MPW-2

Foundry product
EF MPW#2
Reticle set
5CS8007AC
Run date
2021-06-18
Submissions closed
2021-06-18
Projects
56
Fab lot
4205819
Identification
confirmed — Lot records: EF MPW#2, lot 4205819 = 'SKY130 MPW 2'
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-2 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-002/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.