mpw-004 / HVNTM High Volt. N-tip

the HVNTM shapes of all of mpw-004

40 of 40 dies rendered.

542,668 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 (9.5 MB in total, largest 240.6 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-004_HVNTM_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_HVNTM_reticle.png
the stitched reticle, full resolution
5.2 MB ffb9d222bff2201f6934252c6cd62765581f74e95b1988b0edfc71b780583841ba7921d9 ae73b248a42814c356ceb4843a303557763a7a199b2d1bf156e488aa538b8401
mpw-004_HVNTM_reticle_overview.png
the same image scaled to fit 4096 px
359.2 kB 797c6a021554e555124c9361124b941b9906537f97f006d13c1706df3eb26e73289bb1f3 1a90ecf2d2292ceb1eaef65ac906895f82bc1a83b4cd9a914ad1b30b2803b381
mpw-004_HVNTM_tiles.json
where every tile belongs, and its checksum
13.4 kB c29d058b5586647725bf06aea922f9c24b68ef882cbcb73791da01bd5b64599a35d9f84b ea4a7bf135dfff52f9d01fe2df9f7914e3c690ccb79a9d8352b443f578ec266a
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, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 221.0 kB4e9dc584044ad7de8d0a084390917cbfc3995bd700835986abd219cf6e677bb1
A4 pifive-soc 7576×1077622728, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A5 ram_generator 7576×1077630304, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A6 space_controller 7576×1077637880, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
B2 4t1r_testchip 7576×107767576, 10776 220.7 kBef8f949092c669c38d154d188260169d3892306b4ea9cd4e75e6400e983a1d9a
B3 yonga-turbo_encoder 7576×1077615152, 10776 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
B4 icesoc 7576×1077622728, 10776 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
B5 key_value_store 7576×1077630304, 10776 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
B6 subservient-mpw4 7576×1077637880, 10776 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
B7 logic_bist 7976×1077645456, 10776 240.6 kB5d5e4f2138eba6afdcdac07a4a29f84543f581f864e843594654546cede2812d
C1 riscduino-r1 7576×107760, 21552 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
C2 template 7576×107767576, 21552 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
C3 vexriscv_soc 7576×1077615152, 21552 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
C4 ring_oscillator 7576×1077622728, 21552 220.4 kB25b450c5809cba5601c3e905b407e822fbeb7ceb7b2a22855788e2a2a1dac4cd
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 220.4 kB25b450c5809cba5601c3e905b407e822fbeb7ceb7b2a22855788e2a2a1dac4cd
C7 approximate_multiplier 7976×1077645456, 21552 240.6 kB5d5e4f2138eba6afdcdac07a4a29f84543f581f864e843594654546cede2812d
D1 icd_fast_nu_mpw4 7576×107760, 32328 220.4 kBea242e80667b018dc5c62da85653739d4b263c90eaa1d34998f4e5c95ed19723
D2 rram_testchip 7576×107767576, 32328 220.4 kB25b450c5809cba5601c3e905b407e822fbeb7ceb7b2a22855788e2a2a1dac4cd
D3 rest 7576×1077615152, 32328 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
D5 sky130_radtol_test_chip 7576×1077630304, 32328 220.4 kB25b450c5809cba5601c3e905b407e822fbeb7ceb7b2a22855788e2a2a1dac4cd
D6 two_stage_cmos_opamp 7576×1077637880, 32328 220.4 kB25b450c5809cba5601c3e905b407e822fbeb7ceb7b2a22855788e2a2a1dac4cd
D7 ks-guitar 7976×1077645456, 32328 240.6 kB5d5e4f2138eba6afdcdac07a4a29f84543f581f864e843594654546cede2812d
E1 ks-guitar-2s 7576×107760, 43104 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
E2 yifive_a2 7576×107767576, 43104 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 220.4 kB25b450c5809cba5601c3e905b407e822fbeb7ceb7b2a22855788e2a2a1dac4cd
E5 junga_soc_mpw4 7576×1077630304, 43104 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
E6 ibtida-ii 7576×1077637880, 43104 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
E7 azadi_ii 7976×1077645456, 43104 240.6 kB5d5e4f2138eba6afdcdac07a4a29f84543f581f864e843594654546cede2812d
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 240.3 kBfd122d7fc0a470a5216c3e2ea1c01c07cc64fd2d27dcb6d60450bc1c0747a617
F2 current_starved_vco 7576×111767576, 53880 224.4 kBb5a40a09840c3da7cbfe0e811756d8cc205e7ef76cf40c84a447f4d01377d6f7
F3 updown_counter__test_ 7576×1117615152, 53880 240.3 kBfd122d7fc0a470a5216c3e2ea1c01c07cc64fd2d27dcb6d60450bc1c0747a617
F4 skullfet 7576×1117622728, 53880 224.4 kBb5a40a09840c3da7cbfe0e811756d8cc205e7ef76cf40c84a447f4d01377d6f7
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 224.4 kB8e78152f8f223ad99e090d90992f25b20f3966066e371ad46fcfecac27074b69
F6 kasirga_k0 7576×1117637880, 53880 240.3 kBfd122d7fc0a470a5216c3e2ea1c01c07cc64fd2d27dcb6d60450bc1c0747a617
F7 iotestvehicle 7976×1117645456, 53880 229.9 kB3fc9a6a50b5429e249bc27a8c6cd1a1a5fc2d8866617867f70703fce85a78b1a

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 HVNTM on mpw-004

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

Mask layer
HVNTM — High Volt. N-tip
Process step
68 — HV N-tip mask formation
Drawn layer
125:20
Derived from drawn layers as
125:20 OR ((65:20 AND 93:44 AND 75:20) NOT 81:2)
Layer on the mask-layer GDS
39:0
Detail
drawn hvntm merged with a created part (ndiff AND hvi, outside areaid.ce); 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.