mpw-004 / INDM Inductor-TLM

the INDM shapes of all of mpw-004

40 of 40 dies rendered.

12,215,241 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 (37.1 MB in total, largest 3.8 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_INDM_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_INDM_reticle.png
the stitched reticle, full resolution
21.8 MB 52c3fc50bd5ec65131315581a1fafac2a9f72f776c6a7558513f05bae5d767678cfd04bc f9fa443b28fa75bf906f86ccb68c70ce1e2559e715e31c06a32b2aef5fcc1333
mpw-004_INDM_reticle_overview.png
the same image scaled to fit 4096 px
1.9 MB f965e262578d56274e38f06bec428b0f9b9a58ba82c840e7d0aac810d8d63f137aa1dce5 79e2c493d55adef3b8ee45e0722b530a44d6092c9f0906deacd6317bb84df810
mpw-004_INDM_tiles.json
where every tile belongs, and its checksum
13.4 kB ae785ef4a5687ad9f0eb94125b9b0f66a42034dde8f8c823abd7ad627cc6fd9394b1c67d b9549df2f02a3f447d24a484e99786b8523579edbc4557b86e18ee328087a56b
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 1.2 MB39df9c58f3dc0180396295bd88540c85d7b6bb6f635be4afeba1c4526c15aaa1
A2 zero_to_asic_course_mpw2_re-run 7576×107767576, 0 965.6 kB908961a0e081d6d22f1e1f3d804d1bd4492429db6e6e440e5301bcea4412349f
A3 cmos_only_self-biased_current_source 7576×1077615152, 0 670.0 kBf521592494421420b9d96f17e944990dc2784e109a5acc94a85f27f121b65a22
A4 pifive-soc 7576×1077622728, 0 788.8 kB929bb85aff4d8cb12ace160a2de1a92542393d090317b5438025a8b124ad5c22
A5 ram_generator 7576×1077630304, 0 820.7 kB0a7cb8b29512218ab9f5a91c8e3aac2b0898e944851b4d7011786ec75f1f1e82
A6 space_controller 7576×1077637880, 0 740.2 kB146145c4a0df55b6b6a17e4e859b8ea21b167b810a9729d586587e27bd17d118
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack_b1 7576×107760, 10776 740.5 kB5af1210de5cf9d15b2095157f3f6c00c14ec4fb6767c435e0536f16b54cdec64
B2 4t1r_testchip 7576×107767576, 10776 669.7 kB62abe4b47e3856a0ae1f1e1569cb2f6d923632062769d78c2c25917fe59d6b63
B3 yonga-turbo_encoder 7576×1077615152, 10776 895.1 kB181f1803ad52ccbfa28d5a4b2c48033657303979c5c335e381d0a26b8a06ccf3
B4 icesoc 7576×1077622728, 10776 3.8 MB4dd2a8666ca4d4982a8049c7a169b60a7916e826a337f090485bd51c1215eb9e
B5 key_value_store 7576×1077630304, 10776 737.5 kB3e45fc0c7b0bb7ce0d31b24359117ca607248687ff942d4cbecb762a97713393
B6 subservient-mpw4 7576×1077637880, 10776 790.1 kBa970d7b57f4563ad7f31487d6106e466e33b3707085d30c5c1cfb93f8711e8cb
B7 logic_bist 7976×1077645456, 10776 1.2 MB736d855ae85711559d313d0cf8917f857beb96e44f3d090a09480a1e0fca7a3c
C1 riscduino-r1 7576×107760, 21552 1.2 MBf0eb66596420471e908284c9f58b466161a0d0c315dace0bf7572f848f2b846b
C2 template 7576×107767576, 21552 708.7 kB9b74a6ecc06570a755ce7508c7a2a0502b5defc200779f1b37b56421e46adc17
C3 vexriscv_soc 7576×1077615152, 21552 855.1 kB77e3d4b7d781a176934b323497242e6ce774e8bb5434633ad0dbc3d988dca6b9
C4 ring_oscillator 7576×1077622728, 21552 670.0 kBdc398fd28b8131423a07a250caeba583ce4a7b5474f7e93a03c965f5c928a5cf
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 an_mssro-based_vcro 7576×1077637880, 21552 671.0 kBd9da8b444a6a1e6144baf327a6ec6c9b0881d49d84caf18433a7caf68e8eefe8
C7 approximate_multiplier 7976×1077645456, 21552 709.5 kB2b72ded4ee2d4c9b28334b02553f863899c3c82dbd8cc2f4fb148928a8ba1575
D1 icd_fast_nu_mpw4 7576×107760, 32328 670.8 kB49e75880b4db1a8932a9d20578c825a437d21ec80fc30c763d8a168fe2a43490
D2 rram_testchip 7576×107767576, 32328 893.0 kB477fa8ec9b0883545eab6cdfcc288fac4b3b7654fb756181ac4d06aa136c7297
D3 rest 7576×1077615152, 32328 1.3 MB7c9fd04794b7a6570aa37809fa0d211c9cf9c7f04b8398fbea295a4374ea0e5f
D4 fault_tolerant_16-bit_alu_design 7576×1077622728, 32328 697.5 kB421f670e4bbff883abb4c7aba42d8cd5ea2dcfb84a520f331d12e37eb891f395
D5 sky130_radtol_test_chip 7576×1077630304, 32328 733.6 kB7fb1a4c15cab278de67bfd1d3d6f9ad9420cc825f3cd554bbc37e3584aafdaa0
D6 two_stage_cmos_opamp 7576×1077637880, 32328 669.1 kB76e12bf7031c76b8ee9b84774040b1462164c16ca8c5060c3e6ebe51a0e2a56a
D7 ks-guitar 7976×1077645456, 32328 811.1 kB111e0b05f105dbe8f9dd2e2317775ac253e9e1ae4c398b4b1a87216603ecc6c0
E1 ks-guitar-2s 7576×107760, 43104 894.6 kB76629dfcd0127a6b377249bf1821a405cd816e2e3b7a8c76199a3a5913faa1c6
E2 yifive_a2 7576×107767576, 43104 1.2 MB5a087505c73b6a4dddffcce6729a383b3624350db30eec52732644a98723c68b
E3 coriolis_test_soc_-_mpw4 7576×1077615152, 43104 767.9 kB32ceb3c5ccd6e5cc6c7afea9bdd0ca0215bcaf2ee173dde3919fe9de62faa87c
E4 sar-adc_and_analog_circuits 7576×1077622728, 43104 679.6 kB73dc227a9342cb9d25d3cdc3e425fb70d101b6e5cd6e615831ad689e4374ea32
E5 junga_soc_mpw4 7576×1077630304, 43104 859.1 kB232b892dd3dd066c82945a114dd5edb67e91a6244c270080e2dd8756df418f42
E6 ibtida-ii 7576×1077637880, 43104 1.1 MB2692d03f7222f9af07e790ee03655c7660c8d5b0714712fc5f54bf988cddaa22
E7 azadi_ii 7976×1077645456, 43104 1.3 MB860bf39a0eb14c87fb163b8c4c03b10a44a20a5a8477b6cdf826e09c16321b66
F1 open_source_configurable_fpga_fabric 7576×111760, 53880 1.2 MB65e3c36dd25fe79ccbdb1e48bed98f41041d8f404005de6a3def8bdb24da2cb6
F2 current_starved_vco 7576×111767576, 53880 673.1 kBa1abd0813f87e05a9634a390009c857325f59551b77f07a1b4ee15d038f8c3f1
F3 updown_counter__test_ 7576×1117615152, 53880 710.2 kB226390aafe00c95fe8db38f9a58068bc569072b0ddd4b2b8a515c35f7293e22e
F4 skullfet 7576×1117622728, 53880 675.4 kB44e3a95231c0a0c3a82d3375ad740b9d9afeac4a7291dd6a377f75b70bdc2590
F5 cmos_rail-to-rail_comparator 7576×1117630304, 53880 673.4 kBd5d4f40095a3f98c5fafd4c381f5bb793dc72f0993c92dfb2f859fe4b83afb3f
F6 kasirga_k0 7576×1117637880, 53880 880.6 kBedafb27ccf1d3db141d9278dafb2ed80a3ab92f5953c5933c22c59e9d05e7101
F7 iotestvehicle 7976×1117645456, 53880 680.8 kB0e9fbcbeb81c81f0e499eeb36c4cb9ed4153a269c16d3079a35fdf2855d17b99

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 INDM on mpw-004

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

Mask layer
INDM — Inductor-TLM
Drawn layer
70:20
Detail
INDM = met3 (thick-last-metal flow, not SKY130)
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.