mpw-004 / NWM N-Well*

the NWM shapes of all of mpw-004

40 of 40 dies rendered.

25,737,884 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 (21.4 MB in total, largest 1.2 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-004_NWM_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_NWM_reticle.png
the stitched reticle, full resolution
14.3 MB eba7f5505afe32d1d9625c7d50301676c159d636a92730a1867722169d4af3bfc27a0ad5 33f5339e301deb11c3da2c53b3ce2dd35944c33afd9fa02be42d61ec2d18485a
mpw-004_NWM_reticle_overview.png
the same image scaled to fit 4096 px
1.5 MB 812f30f113861327604700edb4ee6e9e5127a16bf2acff80db17d229d1fd01fbfbf688aa 1933bb4530dd6d18862a7b8205ad62e8c2b318398e7020aa3b9071e24915e869
mpw-004_NWM_tiles.json
where every tile belongs, and its checksum
13.3 kB dddf510ec3c4d045e07a1fdfc083c1a89091fce072469da68a102ff8fa6e96b469157154 49b4525838d9f9730e1f04467de5b0987e4024fac6b82dffeeeea490691eb5ee
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, 0 562.4 kB1b7cc32cdf8f55b5f08bb3b904048ef3eb11533808b1af168abf8187022bcd45
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 525.5 kB0db110b4a233638ef8d80226d66e448b6334f512931be767601333c74d3f488b
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 397.0 kB61592d2f0348afdbd89c11fe41d256bccc8e8efc68bcd045275785f7d802495e
A4 pifive-soc 7576×1077622728, 0 497.6 kB352d25b8ca5875f6cff8e593629321582d2983515eadf5b53198be275f1d1258
A5 ram_generator 7576×1077630304, 0 440.8 kBe898a94aa74fc7cfb06bceb5d3edab7e258ee0c688b347c68587b2985111f203
A6 space_controller 7576×1077637880, 0 446.4 kB38ba71889bf24d2e5595a16818a08f0dbdd8f0f18df8d8fde4d95da5dff55185
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 467.3 kB573890d7a50028d1e059515f2f23d7eaf12998bf577fbe2e4f111e0b141c50d2
B2 4t1r_testchip 7576×107767576, 10776 396.9 kB0938219535cc60c873642224a1f57fefe31846a1f79ea6898c1e2aa3827bab2c
B3 yonga-turbo_encoder 7576×1077615152, 10776 462.3 kB15eef14c84ea3a2ee74a9b65f82fc4e28514dc24fd5ae78917d25c3ddd13b495
B4 icesoc 7576×1077622728, 10776 1.1 MB161a187ea637db695b0f0cbe3e1ce1aee272f1282cbcf436db7be3fb286efdf0
B5 key_value_store 7576×1077630304, 10776 412.2 kBdc9824ae2944529ae505ec7442e34041626599aeca0807e157f5f57f9e800bd1
B6 subservient-mpw4 7576×1077637880, 10776 471.6 kBb4281e499d3c2527d23d9ca1f9b42af76c893db52e1df4bee121e5f64b964c32
B7 logic_bist 7976×1077645456, 10776 551.8 kBdf96547562eada356984a5acf46631bc6132aa2d9236a220cc75f2967f6cbc11
C1 riscduino-r1 7576×107760, 21552 669.5 kB7e2d48f51073fa746e0e84b17206841326164250a86111c9a47db7eb73e7398b
C2 template 7576×107767576, 21552 414.1 kB7d10d0a185d58d9d177cf33a728d2e41568b2b7ddc8a46c709c46c209956954c
C3 vexriscv_soc 7576×1077615152, 21552 504.2 kBcffd1df75f4d4c48a15e28e8e80d606496b3abb19ca3742cbda58737740c71c0
C4 ring_oscillator 7576×1077622728, 21552 396.8 kBa669d1702d1d9745e969cf1d2c31cd6c38097db8aeb3d4fd2bb7e9c5ece2b831
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 396.8 kBb2c9aab2a6a944301ff815eee9cd6fa3c8c5fce01b2cefe1c2e42e7cdd65d7cb
C7 approximate_multiplier 7976×1077645456, 21552 444.3 kB6c1f674f329608bd6848ad57f3d5c0387fd5d0dc3bcd850d03b81b6777eb1546
D1 icd_fast_nu_mpw4 7576×107760, 32328 397.5 kB366ab6b6d5c4a088d3d509d2e6ac592866b436e7d56c3fc711da8e64e879902d
D2 rram_testchip 7576×107767576, 32328 473.7 kB77e48a5f77aace5bdc5c78384f7dbecb46ce06404c73670d0a2a2efe8b0b9a10
D3 rest 7576×1077615152, 32328 604.6 kBa899fef6c87887073104a400471980a74121cc16f39ad08a2b8b530dc80334a3
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 409.8 kB7d04bd9eac9d6f1e7cc91aaf60c623c27da6b88dc1bda30be04cf10421ae37a9
D5 sky130_radtol_test_chip 7576×1077630304, 32328 700.6 kB93ecffb018c740a92b08156b3bc6fe252d573ddebf69d31a755cbbf0bcb7a03d
D6 two_stage_cmos_opamp 7576×1077637880, 32328 396.5 kBdd4752fd4c20cece6d5b32e1d2ccfc9a263ac41ad618f3d14b33d9aa88f3e29d
D7 ks-guitar 7976×1077645456, 32328 668.3 kB4032c4afbfd4bccef4dccea20357183bc80e9c0b2954a4f75a509eb40ba2a0ba
E1 ks-guitar-2s 7576×107760, 43104 1.2 MBbace7e5903b51381c825f705b64b3ed50615f8c71462933d419e3e1c40655ee6
E2 yifive_a2 7576×107767576, 43104 634.0 kBde434721400d4b63c33161dbb34c4ce2d52c2fd4225e52e76945c4db81cdb3d3
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 403.4 kBe9dcc4769ba1eb6d42ca3627e125240772380d047369ffa54c24e465cf3f8248
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 395.4 kB3ac39a796e4e0df4f2d83b07d9fc6b736c969c7908504e69a250bde548c9779a
E5 junga_soc_mpw4 7576×1077630304, 43104 511.8 kB8364d93528ef97def42d05c4e81874e01e11c9e6d76038a8813bf906ac484a63
E6 ibtida-ii 7576×1077637880, 43104 594.7 kBbc621749e9f6233c31ecb405431c7a90de289d41e6aa564f8799476d14dde693
E7 azadi_ii 7976×1077645456, 43104 579.4 kBc80dc58fc65744ffe223e00fd8c29c324e0076532b223585363bb422ecab1278
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 1.1 MBe5e498abf7be912ac6759cb1dc339fad30c2d6d843e731cc4e8bc36ccf768001
F2 current_starved_vco 7576×111767576, 53880 392.1 kB2a4d301f74ea77eedec938a67d1cf8c30851bd4735de13e01d9767d3eeb99daa
F3 updown_counter__test_ 7576×1117615152, 53880 420.8 kB7fa22b3e39269a688b41918b5fdc840dddfc44b20a200575a6ad8831836bda15
F4 skullfet 7576×1117622728, 53880 392.1 kB9d52fab131859c19ec32a4bc6304f570f498d3c55539d18a3c95f2655009a1af
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 400.7 kB8cd169f28cd6e09721cdda1fd8bfe547ea8e744f7fbf21deafb4bb18aead5d05
F6 kasirga_k0 7576×1117637880, 53880 538.5 kB56d0261d050392acbc5752c9f2c50d4f0b15111f1d4f501e200cd6b499e02de3
F7 iotestvehicle 7976×1117645456, 53880 405.5 kB3e4f5e13fa87a5409fc524fbe8119a6323196063b3fc55366ec5b044189aed4d

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 NWM on mpw-004

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

Mask layer
NWM — N-Well*
Process step
17 — N-well mask
Drawn layer
64:20
Layer on the mask-layer GDS
21:0
Detail
NWM = nwell sized (cnwm.3a outside hvi / 3b inside), with DEPMOS/pwell-resistor exemptions
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.