mpw-008 / VIM3 Via3-PLM

the VIM3 shapes of all of mpw-008

40 of 40 dies rendered.

65,502,925 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 (17.9 MB in total, largest 828.7 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_VIM3_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_VIM3_reticle.png
the stitched reticle, full resolution
14.0 MB c183d3356a52e1320da70f970f27d783a38e9fd46e99289cec104239f61e46ef6d18b7b2 8ab213fc9e79f73ea40b7a13357e74955e28c58dfc688bb1d65466f175e5ee5e
mpw-008_VIM3_reticle_overview.png
the same image scaled to fit 4096 px
625.3 kB 728cd4f57bd34c7b771c45944adee627be95bc5103dd0329a49e115c11653432d33e8da0 4148e097c8bb58c7051d0d841eeae7d7a71b79c3fdf90e1b1b196d2a2ea3f529
mpw-008_VIM3_tiles.json
where every tile belongs, and its checksum
13.5 kB 72b6cfd641b16db9198c57d52162d6b94f9ac3b68b9fc97b9972969e4bafe3676a9bcd61 721b137a14665c21713e3cdab518d068467c75448cf7936f19d1aa368e50b85a
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, 0 404.9 kBcb0e564938f39be6149d1125dce0365ff9ee9f2ad8dc2edac92ed43cb16147c3
A2 iit_indore_mm 7576×107767576, 0 348.4 kB2d6f85f8e290eb636a66280c173249c7ef115e4a8cc5e5a0e6dab6959ccbd81d
A3 energy_efficient_sum-of-products_circuit 7576×1077615152, 0 356.0 kB4ae0c2a835efd9968122aa70faf0b5fadfa124472bf611365f104de8e69bbe01
A4 riscduino-dcore_d4_ 7576×1077622728, 0 602.4 kBf30642135bbce406023a12e5cafeb1325c13227d5c9a64e12772431aecbbf0be
A5 riscduino-qcore_q3_ 7576×1077630304, 0 643.1 kB209b3e98022dae82f6bcb6b5aea617d5da67c69e665a5d0f5d69252d19e17578
A6 caravel_mpw8 7576×1077637880, 0 356.3 kB32e16bb83c12405987a7e5e47144ce766f02e3ab61f7e1d9102b56edcf24a3cc
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 nanofabrication_project_using_openfasoc_mpw8 7576×107760, 10776 468.5 kBb43a598634915a5698409804aa348f81cbce02e871cbe4c7e90efba44000ca25
B2 sramtestvehicleg4 7576×107767576, 10776 324.4 kB5e579c5cccd3f3dd9adb2f2111edfe32656379cf1c1457c7cba02cf7a6087dba
B3 reram_crossbar_rerun 7576×1077615152, 10776 828.7 kBc9edd32ccf80fd0dac4168b49d0b8c4c8bc3a41c61450cb017516e71e29b414b
B4 tinytapeout_skullart 7576×1077622728, 10776 548.5 kBb65d06dfc4f96d893c056db151fef381ad5363cf8254a8b586af3508e0a46069
B5 soomrv__mpw-8_ 7576×1077630304, 10776 635.1 kB2673f8f28af76d5676f738b045a7f824540997fd3c73d077fd4a65259a5b3ef9
B6 clock_divide_selector 7576×1077637880, 10776 345.9 kBf0495cc5bd2925fa50e84ae88d550b6fbae15d2ee6ea0670a1f211833016ccc1
B7 reram_module_mpw8 7976×1077645456, 10776 357.1 kBa7c5173ab293ae19285858c0c3a9a859af8c553f268e13c75cf2f852f1a19c2f
C1 shapingthewaves_8 7576×107760, 21552 553.9 kB2fd23905be8bf1091c6cdcd8a4bca64522a891f52ea1ec8201e0e3ee619564b8
C2 leosoc 7576×107767576, 21552 550.2 kBfa54df30ad17b3818f83df23b558cb6927b55f34655af3382c1469737d9df840
C3 decrypt_aes128 7576×1077615152, 21552 456.2 kB8ef777d07edafc2a32ad2acedf8b3a870bbf3a933164389d761c963f34dfb243
C4 approximate_adder_axha 7576×1077622728, 21552 356.2 kB428ee7fbdd584fe4f8a49be3b6ac9a60ba5bd4b21ac594851bd9b975562791e9
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 riscduino-pxt1 7576×1077637880, 21552 487.2 kBa60d090f98d43bb7f1dd401ddd0f7da5a21b4ef04602f582c3748288a4b748a9
C7 fitbit_project_using_openfasoc 7976×1077645456, 21552 341.4 kBbf7972ac830a9f8236139175fd510264ce16945a8fbfeb964d994706063fd71b
D1 rift2go_2320_sky130_mpw8 7576×107760, 32328 572.0 kB7b66679e88cf169dc899570fe2e92f7e3749c89f3905f3809e895e2cebc4b6f6
D2 hyperram_controller_for_sky130 7576×107767576, 32328 350.6 kB103eacf53123cc832789879074ebceb31fc6af5df30734eb48274a3ca33f25ca
D3 hardened_alu 7576×1077615152, 32328 378.6 kB11889bfa9a3dda30ee8d39fc34367e51d0c527f7f9b6766190e9cc9648d3a87b
D4 an_open_source_hitachi_sh2_for_motor_control_apps 7576×1077622728, 32328 570.5 kBdbb8e5174c5accd84b3f11ca3e78de645d48e288044af25426a91a668febdfa6
D5 mixed_signal_circuits_mpw8_dec14 7576×1077630304, 32328 324.3 kB8191412712e05ba5d9b04dc7280600f19f2649c895f53ec6204bebb523e00528
D6 gf180_vs_sky130 7576×1077637880, 32328 451.2 kB93a935c4a24338ad548c838cc316f8eb60d32369f557ed63f391a1c073c97a70
D7 iiitb_tlc_mpw8 7976×1077645456, 32328 362.4 kB7ebdf4761cfe536d2fc6d0d9d5ec987fc3abc204b7e93b0d677ae1d90c80fa4e
E1 iiitb_sd_mpw8 7576×107760, 43104 356.2 kB04da6a862625895fd46b8de1ab8893bad91cf1944ae59b8732368bb37a2c6bd1
E2 iiitb_sfifo 7576×107767576, 43104 356.2 kBea0d0fde7d5a5025275e591bc301c61da1b29720d929506ddfb5074563155e40
E3 iiitb_alu 7576×1077615152, 43104 356.2 kB51c40b659092489b50e7029da80a11f2d592d1482d3cc21e782f8d73551ba28a
E4 ppcpu2 7576×1077622728, 43104 525.6 kBf06a7c1af481546bd6e8807191a195f955d70725524898595c7046f781d42a76
E5 mega4_reram 7576×1077630304, 43104 657.6 kBd99559bcee88f834e86933017e091117ad443e7cdea569ee4a5594016b3b838f
E6 tiny_user_project_vgaclock_mpw8 7576×1077637880, 43104 349.7 kBfcc22514e25ed244d036458851d938425481b0c47b0e368ca65738b6e9089d52
E7 sky130cla 7976×1077645456, 43104 356.1 kB72d99279433061567198e578582c1463b67e5ebee4e720c367c5a8198321a066
F1 uetrv_esoc_v2 7576×111760, 53880 510.9 kB9b8b1b7fd29494dea5fcc1d3e3866dfeae1207a528d1c89e34cce7b9d66eb0df
F2 sequencedetection1010 7576×111767576, 53880 360.3 kBa3ed67738be10ed027e8a49eeb7217e6f05a2772666ddb0ea3bce39a5f0287ce
F3 testasynctrimux-mpw8 7576×1117615152, 53880 350.5 kB45aa4f709f9e959c76a3c441641176dee2b6f6428fdf62415e79bd40d912c115
F4 iit_indore_dadda_multiplier_mpw8 7576×1117622728, 53880 351.5 kBb5c5800f7b9472696d5856e65d09cd6d51030dea38b391c922d90514abe77e5e
F5 modified_baugh_wooley_multiplier 7576×1117630304, 53880 360.1 kBbedf5fedfdaf2778577c017b43b7219917be22ba0eacdb50cb5d8bdd959317f1
F6 arbiter_puf 7576×1117637880, 53880 351.6 kB31b7b15fd5bc48b50dffa69671a16a7f71604999886d914e9c54b8f85c9c718a
F7 unigate-sky 7976×1117645456, 53880 487.1 kB684f202fb46168f203077975024b6b21c42f6e33aa993584daa6b1c15fcd83ed

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 VIM3 on mpw-008

Resolved: reticle 5CS8017AC, run mpw-008, mask VIM3

Mask layer
VIM3 — Via3-PLM
Process step
144 — Via3 mask
Drawn layer
70:44
Layer on the mask-layer GDS
50:0
Also
Via 3 (M3→M4)
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.