mpw-004 / CAPM Capacitor MiM

the CAPM shapes of all of mpw-004

40 of 40 dies rendered.

434 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 (4.4 MB in total, largest 110.9 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_CAPM_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_CAPM_reticle.png
the stitched reticle, full resolution
3.5 MB e78cd9670421cbc7ce9946f474306310a3e8f321f8cddf1ab22675bee01488095b12a46b 50211c2d7605a599f09d48d29b9ca4470a1e525d5f0f5ff66246b9fda607ff9a
mpw-004_CAPM_reticle_overview.png
the same image scaled to fit 4096 px
15.5 kB 01353d2fc5621ce3188b89321f7e3569c88de90a8a1ed6c576ecf70dbe263ebfb55709e9 3d005ed98a94b6c4153b95be772f4591a7cb2cf4841aebf5c2df8b9df9c131b1
mpw-004_CAPM_tiles.json
where every tile belongs, and its checksum
13.4 kB 19e528966464df2901f55ab6e526af1256094b6aeb8d5c000b63a3bf077c2b4baf2744f7 09126b04e3a078dcf54b14dd68037d7e758ab0df886494944ff3fcc473f55cfe
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, 0 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
A4 pifive-soc 7576×1077622728, 0 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
A5 ram_generator 7576×1077630304, 0 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
A6 space_controller 7576×1077637880, 0 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
B2 4t1r_testchip 7576×107767576, 10776 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
B3 yonga-turbo_encoder 7576×1077615152, 10776 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
B4 icesoc 7576×1077622728, 10776 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
B5 key_value_store 7576×1077630304, 10776 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
B6 subservient-mpw4 7576×1077637880, 10776 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
B7 logic_bist 7976×1077645456, 10776 106.9 kB293f7b3bb80ecc8189b598f4d0936a4ee71b39727ca6a3f6013d6d774509850c
C1 riscduino-r1 7576×107760, 21552 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
C2 template 7576×107767576, 21552 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
C3 vexriscv_soc 7576×1077615152, 21552 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
C4 ring_oscillator 7576×1077622728, 21552 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
C7 approximate_multiplier 7976×1077645456, 21552 106.9 kB293f7b3bb80ecc8189b598f4d0936a4ee71b39727ca6a3f6013d6d774509850c
D1 icd_fast_nu_mpw4 7576×107760, 32328 105.4 kB64ad568d782b256ebfc745fead217e6fdddfab9c95a6cdac98d70aec18b5cec9
D2 rram_testchip 7576×107767576, 32328 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
D3 rest 7576×1077615152, 32328 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
D5 sky130_radtol_test_chip 7576×1077630304, 32328 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
D6 two_stage_cmos_opamp 7576×1077637880, 32328 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
D7 ks-guitar 7976×1077645456, 32328 106.9 kB293f7b3bb80ecc8189b598f4d0936a4ee71b39727ca6a3f6013d6d774509850c
E1 ks-guitar-2s 7576×107760, 43104 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
E2 yifive_a2 7576×107767576, 43104 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 104.5 kBb48d88cc7781c08dd167bf87e5616a370875eb935af867e2e2d5118fb1139315
E5 junga_soc_mpw4 7576×1077630304, 43104 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
E6 ibtida-ii 7576×1077637880, 43104 102.9 kBa0dbd42a8e3b2535aea82ed594c78cf0746bdbfac6522550c6e0f58882dce2af
E7 azadi_ii 7976×1077645456, 43104 106.9 kB293f7b3bb80ecc8189b598f4d0936a4ee71b39727ca6a3f6013d6d774509850c
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 106.7 kBb2d0c106177c99cb6a58b0f92661ce84240bd93274f4d79f662ff5a6a8b7593b
F2 current_starved_vco 7576×111767576, 53880 106.7 kBb2d0c106177c99cb6a58b0f92661ce84240bd93274f4d79f662ff5a6a8b7593b
F3 updown_counter__test_ 7576×1117615152, 53880 106.7 kBb2d0c106177c99cb6a58b0f92661ce84240bd93274f4d79f662ff5a6a8b7593b
F4 skullfet 7576×1117622728, 53880 106.7 kBb2d0c106177c99cb6a58b0f92661ce84240bd93274f4d79f662ff5a6a8b7593b
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 106.7 kBb2d0c106177c99cb6a58b0f92661ce84240bd93274f4d79f662ff5a6a8b7593b
F6 kasirga_k0 7576×1117637880, 53880 106.7 kBb2d0c106177c99cb6a58b0f92661ce84240bd93274f4d79f662ff5a6a8b7593b
F7 iotestvehicle 7976×1117645456, 53880 110.9 kB5fbd4417aa5c04604eca90097c7419b94a4f810eb592fea229db184fd64d801c

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 CAPM on mpw-004

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

Mask layer
CAPM — Capacitor MiM
Process step
137 — Capacitor mask
Drawn layer
89:44
Used in SKY130
no

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.