mpw-008 / PDM Pad (scribe protect)

the PDM shapes of all of mpw-008

40 of 40 dies rendered.

5,409 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 (4.8 MB in total, largest 124.4 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_PDM_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_PDM_reticle.png
the stitched reticle, full resolution
3.7 MB 624524138e41d8f799f9e753db165beb8ee86e0e3464f8e30d512b839f2a4ddcfd6f0798 7f7c9a0b735d7f943ebff556a1b157ee3d478babb5c5dd4cd98c231b0e41cfc7
mpw-008_PDM_reticle_overview.png
the same image scaled to fit 4096 px
86.3 kB 08af23be1d2986d63057491a48e2c6e6b58e90a4cb2a0ff2d51eb1869fc594be388ba62b 7f0796548dcba01ad8432ec63f9b0b8884993c41cc893c3c87b55614e82942d8
mpw-008_PDM_tiles.json
where every tile belongs, and its checksum
13.4 kB c66eba2f6d4265ac3ae2727e184896606a83e9641ec293a39a9ebd8a80101e4e78fca1b7 29c11590f9d03565f038a1f235674f86ae0ea5757cc01329b779c32f5daa6072
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, 0 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
A2 iit_indore_mm 7576×107767576, 0 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
A3 energy_efficient_sum-of-products_circuit 7576×1077615152, 0 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
A4 riscduino-dcore_d4_ 7576×1077622728, 0 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
A5 riscduino-qcore_q3_ 7576×1077630304, 0 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
A6 caravel_mpw8 7576×1077637880, 0 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 nanofabrication_project_using_openfasoc_mpw8 7576×107760, 10776 124.4 kB4597a1994344b5cbdfa0e88ea46d52427186247f6a292c8cc0e12e895a61005f
B2 sramtestvehicleg4 7576×107767576, 10776 112.2 kBb6b1b59b7e20aa8249bc15b3302065eeea15899e2d361689a0258a0a22027ae4
B3 reram_crossbar_rerun 7576×1077615152, 10776 112.2 kBb6b1b59b7e20aa8249bc15b3302065eeea15899e2d361689a0258a0a22027ae4
B4 tinytapeout_skullart 7576×1077622728, 10776 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
B5 soomrv__mpw-8_ 7576×1077630304, 10776 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
B6 clock_divide_selector 7576×1077637880, 10776 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
B7 reram_module_mpw8 7976×1077645456, 10776 116.0 kB8511ad9b300cfe6515a8d884f050d1d00916a83b64539b1b7d01c4bb4b071768
C1 shapingthewaves_8 7576×107760, 21552 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
C2 leosoc 7576×107767576, 21552 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
C3 decrypt_aes128 7576×1077615152, 21552 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
C4 approximate_adder_axha 7576×1077622728, 21552 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 riscduino-pxt1 7576×1077637880, 21552 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
C7 fitbit_project_using_openfasoc 7976×1077645456, 21552 116.0 kB8511ad9b300cfe6515a8d884f050d1d00916a83b64539b1b7d01c4bb4b071768
D1 rift2go_2320_sky130_mpw8 7576×107760, 32328 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
D2 hyperram_controller_for_sky130 7576×107767576, 32328 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
D3 hardened_alu 7576×1077615152, 32328 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
D4 an_open_source_hitachi_sh2_for_motor_control_apps 7576×1077622728, 32328 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
D5 mixed_signal_circuits_mpw8_dec14 7576×1077630304, 32328 112.2 kBb6b1b59b7e20aa8249bc15b3302065eeea15899e2d361689a0258a0a22027ae4
D6 gf180_vs_sky130 7576×1077637880, 32328 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
D7 iiitb_tlc_mpw8 7976×1077645456, 32328 116.3 kB0b6fc7317dd24588d7de08fcf82c35ec8f3362ec3dddf7d84d8d9d1ec2101a8a
E1 iiitb_sd_mpw8 7576×107760, 43104 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
E2 iiitb_sfifo 7576×107767576, 43104 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
E3 iiitb_alu 7576×1077615152, 43104 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
E4 ppcpu2 7576×1077622728, 43104 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
E5 mega4_reram 7576×1077630304, 43104 112.2 kBb6b1b59b7e20aa8249bc15b3302065eeea15899e2d361689a0258a0a22027ae4
E6 tiny_user_project_vgaclock_mpw8 7576×1077637880, 43104 112.4 kB8b3e83c7e04f25e37ce8731f3e507e85669fdbcd354dc0366c6cdf779748cd98
E7 sky130cla 7976×1077645456, 43104 116.3 kB0b6fc7317dd24588d7de08fcf82c35ec8f3362ec3dddf7d84d8d9d1ec2101a8a
F1 uetrv_esoc_v2 7576×111760, 53880 116.2 kBd10962219cbe861e700172c53f7c02735c4bdafa504055669e433e36532e4e5d
F2 sequencedetection1010 7576×111767576, 53880 116.2 kBd10962219cbe861e700172c53f7c02735c4bdafa504055669e433e36532e4e5d
F3 testasynctrimux-mpw8 7576×1117615152, 53880 116.2 kBd10962219cbe861e700172c53f7c02735c4bdafa504055669e433e36532e4e5d
F4 iit_indore_dadda_multiplier_mpw8 7576×1117622728, 53880 116.2 kBd10962219cbe861e700172c53f7c02735c4bdafa504055669e433e36532e4e5d
F5 modified_baugh_wooley_multiplier 7576×1117630304, 53880 116.2 kBd10962219cbe861e700172c53f7c02735c4bdafa504055669e433e36532e4e5d
F6 arbiter_puf 7576×1117637880, 53880 116.2 kBd10962219cbe861e700172c53f7c02735c4bdafa504055669e433e36532e4e5d
F7 unigate-sky 7976×1117645456, 53880 120.3 kBf969326ccac88723beaad009063417ca0ebce161dbe2e02c20cc92fa4c1e36ff

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 PDM on mpw-008

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

Mask layer
PDM — Pad (scribe protect)
Process step
168 — Pad mask
Drawn layer
76:20
Layer on the mask-layer GDS
37:0
Variants
Pad (scribe protect), Pad (scribe unprotect)
Detail
PDM = pad OR (cpmm AND areaid.mt) sized by cpdm.4
Used in SKY130
yes

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.