mpw-004 / CAP2M Capacitor mask

the CAP2M shapes of all of mpw-004

40 of 40 dies rendered.

54 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_CAP2M_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_CAP2M_reticle.png
the stitched reticle, full resolution
3.5 MB e1ca34a3b942f51b390ffc9d5d03c5f2387185b2b976e61a11f174098dc04697ba60e162 c2b8d39c7ae9f97dd12e7e3ce6389cbb5cf65dc5c3105171b0234b4c0c28eff2
mpw-004_CAP2M_reticle_overview.png
the same image scaled to fit 4096 px
14.5 kB 26876d3912cfb3694540f08656a9e8b386847c60d0f7ac30c52615b22e9fd0e9c4525c75 a1c4783e6faee9895dda070bb218ffab5554ee3a1385b391b6eae1ba4300d80b
mpw-004_CAP2M_tiles.json
where every tile belongs, and its checksum
13.4 kB 8689b60fe21ac5d3249fb6a26702cb2bc1e92a88e59673f38f831c91af60564711c6f842 5eb6e4d3f401afd45513a1f6a8ab5564cbe7b1a20446c014ff14b5395d196dce
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 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
A4 pifive-soc 7576×1077622728, 0 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
A5 ram_generator 7576×1077630304, 0 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
A6 space_controller 7576×1077637880, 0 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
B2 4t1r_testchip 7576×107767576, 10776 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
B3 yonga-turbo_encoder 7576×1077615152, 10776 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
B4 icesoc 7576×1077622728, 10776 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
B5 key_value_store 7576×1077630304, 10776 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
B6 subservient-mpw4 7576×1077637880, 10776 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
B7 logic_bist 7976×1077645456, 10776 106.9 kB60ca2196d8ee88e8743dee718a892b494aa1384fc91ecb15b30d24679dbbd62d
C1 riscduino-r1 7576×107760, 21552 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
C2 template 7576×107767576, 21552 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
C3 vexriscv_soc 7576×1077615152, 21552 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
C4 ring_oscillator 7576×1077622728, 21552 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
C7 approximate_multiplier 7976×1077645456, 21552 106.9 kB60ca2196d8ee88e8743dee718a892b494aa1384fc91ecb15b30d24679dbbd62d
D1 icd_fast_nu_mpw4 7576×107760, 32328 103.4 kB401ad5922266ec7abb74dca8eca7727441c8e4edcbaa6e6781f909a9db38a961
D2 rram_testchip 7576×107767576, 32328 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
D3 rest 7576×1077615152, 32328 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
D5 sky130_radtol_test_chip 7576×1077630304, 32328 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
D6 two_stage_cmos_opamp 7576×1077637880, 32328 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
D7 ks-guitar 7976×1077645456, 32328 106.9 kB60ca2196d8ee88e8743dee718a892b494aa1384fc91ecb15b30d24679dbbd62d
E1 ks-guitar-2s 7576×107760, 43104 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
E2 yifive_a2 7576×107767576, 43104 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
E5 junga_soc_mpw4 7576×1077630304, 43104 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
E6 ibtida-ii 7576×1077637880, 43104 102.9 kB9b0aeae35c7144155b07a1c5523bf24a8df5090971ab36c4d234d3ced6633c8b
E7 azadi_ii 7976×1077645456, 43104 106.9 kB60ca2196d8ee88e8743dee718a892b494aa1384fc91ecb15b30d24679dbbd62d
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 106.7 kBbe2094b091fea5063fa1ca18b9345c3fcc68f1906a346b29248e6851741c50f6
F2 current_starved_vco 7576×111767576, 53880 106.7 kBbe2094b091fea5063fa1ca18b9345c3fcc68f1906a346b29248e6851741c50f6
F3 updown_counter__test_ 7576×1117615152, 53880 106.7 kBbe2094b091fea5063fa1ca18b9345c3fcc68f1906a346b29248e6851741c50f6
F4 skullfet 7576×1117622728, 53880 106.7 kBbe2094b091fea5063fa1ca18b9345c3fcc68f1906a346b29248e6851741c50f6
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 106.7 kBbe2094b091fea5063fa1ca18b9345c3fcc68f1906a346b29248e6851741c50f6
F6 kasirga_k0 7576×1117637880, 53880 106.7 kBbe2094b091fea5063fa1ca18b9345c3fcc68f1906a346b29248e6851741c50f6
F7 iotestvehicle 7976×1117645456, 53880 110.9 kBea0be884384754165c29bf0468e1ee1a1f67ad1c71ab09fb6c962f232b604ebe

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 CAP2M on mpw-004

Resolved: reticle 5CS8010AC, run mpw-004, mask CAP2M

Mask layer
CAP2M — Capacitor mask
Process step
152 — Capacitor mask
Drawn layer
97:44

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.