mpw-004 / VIM2 Via 2-PLM

the VIM2 shapes of all of mpw-004

40 of 40 dies rendered.

33,439,262 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 (24.0 MB in total, largest 1.6 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_VIM2_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_VIM2_reticle.png
the stitched reticle, full resolution
16.5 MB 07cb09858ef7ac636adeb2a1bf08887cd303131178f3672adf987771ec44fe7f68b372ea 8724b8d656a29c7f68820500f9b86f7d8e92f79c39d939a233b97c2e42473406
mpw-004_VIM2_reticle_overview.png
the same image scaled to fit 4096 px
610.1 kB b65975948bfd343d4f913eef25d7029459a009d5ea1a9a36743d40fbe2e336bc39b66417 d92cbba2366ef1b7a20a292c4275db2c389f368171c0b5894bc9922fa4540902
mpw-004_VIM2_tiles.json
where every tile belongs, and its checksum
13.4 kB 078a36ba755ed74807184e7e4caf1ab8a1643e5b67e294c7f441f344d2970de9c6747685 d083308638a6720f8d08f85df61f8a591e4659249ebb00a1b9638fac9ce3c4b3
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, 0 773.3 kB56506954b4e7aad88276a72e6e60af06db2aa5ca8abaaa6ff087b004f076e3ba
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 629.7 kB088e50973efacdff2202dde2e9149d0280c15928a84f178ce087363be59c390c
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 480.8 kBf183493eac452219b995a6795a0ae5d4d2adf7a2a2004299b0eda83712ffd66e
A4 pifive-soc 7576×1077622728, 0 560.6 kBf6523ae54b123149b242a75b4d66b0c4749726b522e25372cef7644c0b2f4766
A5 ram_generator 7576×1077630304, 0 542.0 kB79a94ee7d2ba7d06668915b3695ab0077f554271205e29311addde8b99cd5b8a
A6 space_controller 7576×1077637880, 0 528.0 kBa70b5780b218c1afdebd5a0392846253bc357a403c5cb1cbc8cb913cde4e434f
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 523.9 kB305ca12226d2c8bf50a79e1e4b16afd5ea5ff6a44d308a1a7ca17948314f84d0
B2 4t1r_testchip 7576×107767576, 10776 472.8 kB10770bd00bfad2fe6bb4993f094a2705fe1e49157461ec213ce9846e768b0862
B3 yonga-turbo_encoder 7576×1077615152, 10776 613.6 kB7255651fbd4eeefd4697e896751705049677972ea3b3e8ceb1cf000d1057be8f
B4 icesoc 7576×1077622728, 10776 1.6 MBe33554b0e591a74f60627d3b83292a0ce4b4a15cf378de3225eb3f573bc080b9
B5 key_value_store 7576×1077630304, 10776 517.0 kBc6c5978c16995f839bfabb7f3703d773a3d8b9ea1312abf31604eb20c2e6f267
B6 subservient-mpw4 7576×1077637880, 10776 555.1 kB9287afb65e3025e43286106fc03fc351b3d3950de1613a392c61df73ed8c8793
B7 logic_bist 7976×1077645456, 10776 710.2 kB6952f00fcb6496f103c76589e4febe5e34e145bb16ffcb46ccacfc57458e28e8
C1 riscduino-r1 7576×107760, 21552 718.0 kB6534f1b0760c0bf836202fa356eb635186a3f15b59772f387e7cd5be767b0b1e
C2 template 7576×107767576, 21552 507.8 kBbb655ea13f29c5e0897daaa0d05ac04eddaa9b7cabe434086f83db89633f54b3
C3 vexriscv_soc 7576×1077615152, 21552 565.2 kBa85becb8f9e897e35803a72b2cd6abd3bca1c3c6fa09e711e4963b038678a7b7
C4 ring_oscillator 7576×1077622728, 21552 472.5 kB4cbdd1065bf4d11ce383a070a72c29e5fa2df8851818a633e4850a6a4cd620f1
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 473.7 kBf3034d162eaf20201c24899bd778c939d70c067e67dc7cc314e619b0179ed34d
C7 approximate_multiplier 7976×1077645456, 21552 514.1 kBc861a148d245b917dc61dad560fa47df49af0083fefa1bcacea185f0f460a985
D1 icd_fast_nu_mpw4 7576×107760, 32328 475.5 kB1787f5bb8ad03c2796983046364d651794d018a665ef52def51a12c66e65caab
D2 rram_testchip 7576×107767576, 32328 567.6 kBbebb89e0c9f447b927ba7d78fe8c4975356de35cb93dbf826cf980deb2f2a861
D3 rest 7576×1077615152, 32328 724.7 kBec52646f8938ebc9e9d58d38d55b862600d1fef9333f57932b066192ef6bca8d
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 497.0 kBb33e6a50d5402de4793962ba0a4db954261c4a9ca029ddf9ec74b48bac49e5ba
D5 sky130_radtol_test_chip 7576×1077630304, 32328 532.8 kB7318fc86d56361f989fefb0a6b848f5643cc5dd84b7067be439d14d6c1de94ce
D6 two_stage_cmos_opamp 7576×1077637880, 32328 472.3 kBc7ed9efe1f5ee9854e3fe460e6cca4dae152579dec9859496a8498b1cbf27c2f
D7 ks-guitar 7976×1077645456, 32328 595.7 kB1b86a36e48ad2f5d8b4a6541e07270793d13c3b1160ea6830ed21eec0fd03065
E1 ks-guitar-2s 7576×107760, 43104 653.2 kB5f7c842975018a2b98847449464599cbfb3656a149cbdc067ccb946cde1ec90b
E2 yifive_a2 7576×107767576, 43104 723.1 kBa6e004a100b95c785db9fb4ca699997e8fb43e21e6fd0c88e6abb66fb0dddcc6
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 580.6 kBcaa299064ba71f890eba60d0146cf2b1cdd7af66f12a30f33c74b194d7929403
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 478.7 kBe4f946e15efc63aed2cd426dab2a07aaa722ad122cdf6daa764d7675ee2f6231
E5 junga_soc_mpw4 7576×1077630304, 43104 566.7 kBbf48689ac5357a9759f6a2107caa23e5fd9eb93a1e137834fb8a7bd1f1c3878e
E6 ibtida-ii 7576×1077637880, 43104 634.5 kBb9b0c4cc7bee6dc07110237e2834ad71e520785008bc8a81c78fd39b397fdb40
E7 azadi_ii 7976×1077645456, 43104 715.1 kB5df30fd7a2d77801ca245b32c84d7aa05d03d9563ababebff2fad0d8c1368edc
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 810.6 kBb4bed9359ff37da2642bf699b54317435129dee14874276790ceb86e38aa0b00
F2 current_starved_vco 7576×111767576, 53880 475.6 kB40aae6bac0a90245446e7151029839f3541fdfd67798d1928a07210068dd8354
F3 updown_counter__test_ 7576×1117615152, 53880 510.9 kB728710528b30819c1621d1771435f43a29ea21ea76af8337d260c6ceb33409e6
F4 skullfet 7576×1117622728, 53880 475.7 kB46676d4edd3c82b99e32fbb067138b14522e549328c62c744d9bc333f17253a9
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 476.1 kBe6ebca718f3d2e9e7be1f41cee761ce1f95e1b23cd9fbe69f00b5fbf48241640
F6 kasirga_k0 7576×1117637880, 53880 591.8 kBe3c7bc9eb3735756d80e640ca2d1c02130fae0d49a1504681e0bd45d95af32be
F7 iotestvehicle 7976×1117645456, 53880 493.8 kB97807148b41305f0ac8f148f1029abf43b0bf72b6f34450fc98aa11682189ea4

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 VIM2 on mpw-004

Resolved: reticle 5CS8010AC, run mpw-004, mask VIM2

Mask layer
VIM2 — Via 2-PLM
Process step
129 — Via2 mask
Drawn layer
69:44
Layer on the mask-layer GDS
44:0
Variants
Via 2-TNV, Via 2-S8TM, Via 2-PLM
Also
Via 2 (M2→M3)
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.