mpw-008 / INDM Inductor-TLM

the INDM shapes of all of mpw-008

40 of 40 dies rendered.

36,268,487 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 (50.5 MB in total, largest 2.1 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-008_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-008_INDM_reticle.png
the stitched reticle, full resolution
26.0 MB c3e8d8b7e08c9c6881ad4889effed27267502844b760e3a80b384d4d7c104e06af538fb1 52e3d189aa6b78b2668683f8c23cc270892566b77270aaf86251aca4ab6c1e8f
mpw-008_INDM_reticle_overview.png
the same image scaled to fit 4096 px
2.5 MB 282c05d013081a2e067dc0f4327632fda338fc7f5ac82cff7a8f1ec76fe52eb947fea839 f4eed809b9380f021f7811a4c9eb02539b585295c8722d678b9774d45b6f5d77
mpw-008_INDM_tiles.json
where every tile belongs, and its checksum
13.5 kB 3bdbe5401e126c3e08a6f1b17bb55e8425e514d9e9e2049399ab8fb555ef80456e71c63a ea4b2223b8271577d78e4ccfb430d180901e83d3a1c0366ed141b92f012256c2
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 wishbone_pio 7576×107760, 0 1.2 MB5d8e8a713c9ef1400468e05b511ae751713637764900630320532ce25fdf40d6
A2 iit_indore_mm 7576×107767576, 0 1.0 MBe5b477f653369d94e7978f38ada908cc70b41e3f6a6559d91d92cf5d122a2041
A3 energy_efficient_sum-of-products_circuit 7576×1077615152, 0 1.0 MBf703cd86e84fca15076f766a9ea860e773c65fdfc26f0161bdb41bca5d353332
A4 riscduino-dcore_d4_ 7576×1077622728, 0 2.0 MBca54a06b5e8307f678f956fa4985298ef0265cd5ab0f65ecc5a2af8f9ca0383c
A5 riscduino-qcore_q3_ 7576×1077630304, 0 2.1 MBdf13432012425edb53674813515d2ef04b6bf2ef1ad954d2cc12d086f0ee3bb5
A6 caravel_mpw8 7576×1077637880, 0 1.0 MB3798ce2952abcf0c3a2200b3419b11c67ed8790f4c62693466247761745d4ab0
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 nanofabrication_project_using_openfasoc_mpw8 7576×107760, 10776 1.1 MBd20d37a89cb8d532e3b0cbaf1149db4aa6e1b4214d5336cd7eb725247feb7d7a
B2 sramtestvehicleg4 7576×107767576, 10776 967.5 kB210fa347dda326c1b05e5392a71371f829b2895c629532faa6a354d15e262c06
B3 reram_crossbar_rerun 7576×1077615152, 10776 1.6 MBfaf89bae61ca53d7a893685ef498c3dfa0402410b07cc9c2f4dc4bbb4d48a3f9
B4 tinytapeout_skullart 7576×1077622728, 10776 1.6 MBb34413a88386cbef96356a34cb5f428def5b5f0882d1d5eb3bf43538f300aa45
B5 soomrv__mpw-8_ 7576×1077630304, 10776 2.1 MBcbad61414199bc8232b60852f8d7fd7b6b8c3f29660b0d825206b4a0961da8bb
B6 clock_divide_selector 7576×1077637880, 10776 997.8 kB258112f8aab872b169c7699eea6fa62168c08ceb5c99959ca271f2229fe772d0
B7 reram_module_mpw8 7976×1077645456, 10776 1.0 MB51b4850626a8514812eeb5e98b8c40e60cf98ba4b7c32bdf5096248428011820
C1 shapingthewaves_8 7576×107760, 21552 1.5 MB375ed70a5ebfc966990bd9c78086fb17aeb5e9ec222ee2256df349a17ba1fe6d
C2 leosoc 7576×107767576, 21552 1.6 MB032fd11fcbc3a47aea34b0519a82433918d014758451b650a0a5117f4800dd65
C3 decrypt_aes128 7576×1077615152, 21552 1.4 MB00a65cff849e4d44741729cbad915670ab8a35fddb6585e543c3c54b0bcfd6e5
C4 approximate_adder_axha 7576×1077622728, 21552 1.0 MB56e6fd3a8f7b3adc8daf5db709773e24038590376a38ad9f0d1792a81f5d888f
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 riscduino-pxt1 7576×1077637880, 21552 1.4 MB2d46d7a285cfc96736c3fb315cc3386c1192f63df71d9f844dc487c4aa6e0d76
C7 fitbit_project_using_openfasoc 7976×1077645456, 21552 998.4 kB54392dbea669a164939de3ff2edbfeb0ac73dff09b845d792ee2f91b35421bb4
D1 rift2go_2320_sky130_mpw8 7576×107760, 32328 1.7 MBb3c45923ecc719b1a78f2f5703def8e92106d3c69007e7a12ffad61db4993c63
D2 hyperram_controller_for_sky130 7576×107767576, 32328 1.0 MBb640b50b13d6cbb2c6f7be136a3fcaf771b6c9bfa5c319469013a0f14c40fde9
D3 hardened_alu 7576×1077615152, 32328 1.1 MB8f536cdfb0e8fc7bd0fa9f32803c87ff7c9976b2fe1c9cdf9361622e90fa59de
D4 an_open_source_hitachi_sh2_for_motor_control_apps 7576×1077622728, 32328 1.5 MBd7b975f4cdafa6a41f73c943157e1f5fe1f3d97d1a9b22e08724e8d13a57a34c
D5 mixed_signal_circuits_mpw8_dec14 7576×1077630304, 32328 967.1 kB10f2a53cef556b22f6b858238c9b7b72a9bd6788b66770b1f640277cee96a5b2
D6 gf180_vs_sky130 7576×1077637880, 32328 1.4 MB9e612c436a7ea10d51d9e7f05498f4492d21ffd5277a0c205f0fc74fb490916e
D7 iiitb_tlc_mpw8 7976×1077645456, 32328 1.0 MBb6897b64fd9750467cdd7ccd27abe12b982f7cf3b807a848775855bd4a45190e
E1 iiitb_sd_mpw8 7576×107760, 43104 1.0 MBa5d35d9bcd284af4512ba805ae4d094956b84e6ca516785f15167e3c44949fe4
E2 iiitb_sfifo 7576×107767576, 43104 1.0 MB9aad357006ee22def331a6fbe4fa45ad1b4923dfc046a9bcd70856cd4f43a26d
E3 iiitb_alu 7576×1077615152, 43104 1.0 MB913894aeb22c7192102f33ba8a1b44faaff1ee34360d7b5042e0217de1468fa1
E4 ppcpu2 7576×1077622728, 43104 1.8 MB7fed11daf858c0630e4e4aad55ffcb5cd5e1666738ae10e0351b40a08695c30f
E5 mega4_reram 7576×1077630304, 43104 1.4 MBef62cbf517b3eff14ee4399c18bc83432a7451d5b43aed7a5d118f77b7e7ed4e
E6 tiny_user_project_vgaclock_mpw8 7576×1077637880, 43104 1.0 MB5c8d0e3c4268f8db20e174e56d155e02769b31d45ac5775309b3bb568400d5b8
E7 sky130cla 7976×1077645456, 43104 1.0 MB14391843f6ea1a8c50a9367c64a0cefffe0b4f57f6480343105f9a1228738a6f
F1 uetrv_esoc_v2 7576×111760, 53880 1.5 MB55271ed982d4fa6f33115e11d61e3f061ffb2553f1532182e19f1f2ba8bfb083
F2 sequencedetection1010 7576×111767576, 53880 1.0 MB7943836fe3cb83418ce0e25d391d65ebdf7fc6d66fe3a60e22b72e3584214ab5
F3 testasynctrimux-mpw8 7576×1117615152, 53880 1.0 MB9b3e4cef1a418563dbe4e086cd727cd3622c7a972c1ceca2e0696501665154db
F4 iit_indore_dadda_multiplier_mpw8 7576×1117622728, 53880 1.0 MB8937169f1aaec04936a67a36815fa61a65f7c7fff0d0ac1c90f637cb22102a6a
F5 modified_baugh_wooley_multiplier 7576×1117630304, 53880 1.0 MB412b9b44eb51575fb0d24789f02cf42aeadc93f176c0985ba1023e3f32067ff4
F6 arbiter_puf 7576×1117637880, 53880 1.0 MBc06391824cc6a236a1d551bc23e67e0471c5ae6d94a62a0c4bf290c2d7ae6bbb
F7 unigate-sky 7976×1117645456, 53880 1.4 MB37246a20bcaf481e1e948cb4bfb70d8aaa5585287c2dbe3dd8b27d2fa3fe3314

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-008

Resolved: reticle 5CS8017AC, run mpw-008, 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-008 — SKY130 MPW-8

Reticle set
5CS8017AC
Run date
2022-11-19
Submissions closed
2022-12-31
Projects
144
Identification
inferred — Sequence after 8016=MPW-7 (8018 is the re-made MPW-4 set); packing list 2026-08-25
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-8 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-008/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.