mpw-008 / URPM Ultra-high resistor poly mask

the URPM shapes of all of mpw-008

40 of 40 dies rendered.

967 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-008_URPM_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_URPM_reticle.png
the stitched reticle, full resolution
3.5 MB d9ff00afb2a2c9a66f9755d5fe94b40a3916b0126415c8236e211a9aeb1b5167d4152b9f c2627a18d3d7ba54a0439b7e821b380b822eb744764e8482cb2f5e9b50bdc448
mpw-008_URPM_reticle_overview.png
the same image scaled to fit 4096 px
16.0 kB f4199c82f109e34868e0d57756b6a949f5ba056427962e5e480c73da17ec861e10c24b57 ce365e255a075870689b5d2f51dd49af4398151b60291a2b8b27f8e883af50e9
mpw-008_URPM_tiles.json
where every tile belongs, and its checksum
13.5 kB 4b47090c733acbd1fb0c920cb0f9ac7d0160eebb4de4265222b92077f75c0cda1553c3a9 5206b0354300e259a706bb4c57b7f5a54c96833c4ae28b7bd53e42e11341ddc2
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, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A2 iit_indore_mm 7576×107767576, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A3 energy_efficient_sum-of-products_circuit 7576×1077615152, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A4 riscduino-dcore_d4_ 7576×1077622728, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A5 riscduino-qcore_q3_ 7576×1077630304, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A6 caravel_mpw8 7576×1077637880, 0 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 nanofabrication_project_using_openfasoc_mpw8 7576×107760, 10776 109.3 kB05d03db98bf36ddb30a20bb787c96cc05457154567a16705b0da3d69aa282f0e
B2 sramtestvehicleg4 7576×107767576, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B3 reram_crossbar_rerun 7576×1077615152, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B4 tinytapeout_skullart 7576×1077622728, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B5 soomrv__mpw-8_ 7576×1077630304, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B6 clock_divide_selector 7576×1077637880, 10776 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
B7 reram_module_mpw8 7976×1077645456, 10776 106.9 kB24fc4f09b4bd28cada855bff8a84875c9d42464781d49f18223fedf9c060cb09
C1 shapingthewaves_8 7576×107760, 21552 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
C2 leosoc 7576×107767576, 21552 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
C3 decrypt_aes128 7576×1077615152, 21552 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
C4 approximate_adder_axha 7576×1077622728, 21552 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 riscduino-pxt1 7576×1077637880, 21552 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
C7 fitbit_project_using_openfasoc 7976×1077645456, 21552 107.8 kB589f2df51dd1ad5c91cf3218a72c6c67bd55529dd57d3aa474a75f708b0939bd
D1 rift2go_2320_sky130_mpw8 7576×107760, 32328 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
D2 hyperram_controller_for_sky130 7576×107767576, 32328 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
D3 hardened_alu 7576×1077615152, 32328 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
D4 an_open_source_hitachi_sh2_for_motor_control_apps 7576×1077622728, 32328 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
D5 mixed_signal_circuits_mpw8_dec14 7576×1077630304, 32328 103.2 kB45112fcbe6210c1ad0c9c4bbee8fcb2607e5f6ed6556ca5608888c3d77148983
D6 gf180_vs_sky130 7576×1077637880, 32328 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
D7 iiitb_tlc_mpw8 7976×1077645456, 32328 106.9 kB24fc4f09b4bd28cada855bff8a84875c9d42464781d49f18223fedf9c060cb09
E1 iiitb_sd_mpw8 7576×107760, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E2 iiitb_sfifo 7576×107767576, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E3 iiitb_alu 7576×1077615152, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E4 ppcpu2 7576×1077622728, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E5 mega4_reram 7576×1077630304, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E6 tiny_user_project_vgaclock_mpw8 7576×1077637880, 43104 102.9 kBec7014608b651572d2bb9f21d4f0969ce994d0f8f3e0c0a2b1a9c4e2f4cee026
E7 sky130cla 7976×1077645456, 43104 106.9 kB24fc4f09b4bd28cada855bff8a84875c9d42464781d49f18223fedf9c060cb09
F1 uetrv_esoc_v2 7576×111760, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F2 sequencedetection1010 7576×111767576, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F3 testasynctrimux-mpw8 7576×1117615152, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F4 iit_indore_dadda_multiplier_mpw8 7576×1117622728, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F5 modified_baugh_wooley_multiplier 7576×1117630304, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F6 arbiter_puf 7576×1117637880, 53880 106.7 kB3519556765611d90ce00475d414ac90855795d869e456031d86492340d3de707
F7 unigate-sky 7976×1117645456, 53880 110.9 kBf4003129e59f6711282296e4e6ff16c7a66ed7d6da5e53cd32fc7a676a5b7686

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 URPM on mpw-008

Resolved: reticle 5CS8017AC, run mpw-008, mask URPM

Mask layer
URPM — Ultra-high resistor poly mask
Process step
55 — Ultra-high resistor poly mask
Drawn layer
79:20

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.