mpw-003 / VIM4 Via4

the VIM4 shapes of all of mpw-003

40 of 40 dies rendered.

10,192,955 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 (28.8 MB in total, largest 780.2 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-003_VIM4_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-003_VIM4_reticle.png
the stitched reticle, full resolution
11.5 MB e673c149ac3dc4fc80932934a282de78f7f595810c817889a3b4797b80a8ce72b6d77e01 515a99b687661f0325b3b12d7c6910a14658d84022eadc7ecff1be19713e9965
mpw-003_VIM4_reticle_overview.png
the same image scaled to fit 4096 px
559.3 kB cc1ad3e1ff793434999faf5d77d23179a3b744ff570452061457790f5e203d239b5051a1 95350020329b012f6ae38c875652980b25f41ec098a9c4154c05adf6c0bcb1aa
mpw-003_VIM4_tiles.json
where every tile belongs, and its checksum
13.5 kB c123704571308f939b42ecd0f3d01f9aa5fc2ffbddfb3ea504e225ca178504d54c3ec295 f4998ed1bcf13d7eacd0758fc6800189fe2752f0ca7ec20c484f856324b56404
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 stdcelllib 7576×107760, 0 720.8 kB08ca40b06bac693bc723f4139fc043e61359d1ac29a897f08740eff7ad0db7eb
A2 1v8_ldo_design_in_skywaters_130nm 7576×107767576, 0 680.0 kB4b4ef7e949229987c281b3f1ac94efb22a9909d7744ebfc06ecadab9ca617e25
A3 openram_test 7576×1077615152, 0 721.8 kBa88dd7c61efda53e0c6cd9696c736f5cfd32a200a9b0b8a1c44bbef587aa8c49
A4 zero_to_asic_course_group_submission_mpw3 7576×1077622728, 0 722.3 kB8bfb9a8ce16844e7cb549e10b461a059b4ec96bdb342dd39007d2cc5864e6a6b
A5 crypto_accelerator_v2 7576×1077630304, 0 721.2 kB20505eb23b901908d4a9040754ea6f057a612c4b1091a40d28055ff51b186352
A6 picorf0 7576×1077637880, 0 721.8 kBe07048f3774bcf228bd7d9ea364056ab4d1f22b12490e419b93a6c28daaf92fb
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 randsack 7576×107760, 10776 721.6 kBc7df58e9ca7e09d69a95d648de1ed4e12864a97cc1831a37f67aa2572804663e
B2 yonga-100m_ethernet 7576×107767576, 10776 721.8 kBe07048f3774bcf228bd7d9ea364056ab4d1f22b12490e419b93a6c28daaf92fb
B3 approximate_multiplier 7576×1077615152, 10776 721.9 kBbe59510e01c277f96180b2d123a72145657183b279d5fa070be695b71df23834
B4 vsd 7576×1077622728, 10776 701.5 kBcbdad9e74303b607a6570df39d56d6fdad966ed81c45559878145f3cebecc2e3
B5 asic_key_value_store 7576×1077630304, 10776 720.8 kB08ca40b06bac693bc723f4139fc043e61359d1ac29a897f08740eff7ad0db7eb
B6 mbist_controller 7576×1077637880, 10776 720.2 kBe101412ba3f9eebb7e7fc80f200ac2e3560b0c5d6c7a85c5fdbbedd6c79871ff
B7 riscduino 7976×1077645456, 10776 765.6 kBd31f2e438e4aef1db6bad74614028b0d047979b5dcfafcb7a640594f169b0e31
C1 caravel_peripheral_extender 7576×107760, 21552 721.0 kB25f93f45c94383eaf3a10e99ebb218ac73b564c01b9c3d15bb8cc400acba6f1c
C2 ucsc_openram_test_chip_v2 7576×107767576, 21552 717.7 kB2409765897d48e433a4de70c086ebd2f05142463bed2c68d056c0aea90ff8a80
C3 class-d_audio_amplifier 7576×1077615152, 21552 780.2 kB78e44dc1d28c2d75fc2e9b2ae006acd903f6edf8550d122f12dfb2e4c0fc0c48
C4 efabless_processor 7576×1077622728, 21552 720.8 kB08ca40b06bac693bc723f4139fc043e61359d1ac29a897f08740eff7ad0db7eb
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 tooltest 7576×1077637880, 21552 721.6 kB55df4152d9f941173c9f29420ae089d9f70180051e198dee812f3e36aa69bfc7
C7 comparator_and_mixed_signal_test 7976×1077645456, 21552 677.1 kBf3355fa7efb1c9ae0f9afb5cf8de8ba712384904e72db1fbe0a3855f733e8a84
D1 current_starved_voltage_controlled_oscillator 7576×107760, 32328 661.5 kB7577b5df932f7753cb73512dde4c004436fb5b47e343b13b46ad8ebd7c980624
D2 two_stage_cmos_operational_amplifier 7576×107767576, 32328 661.3 kB58739af58c19dfb6a76581f752a199fc0dcd6ac6541f83bc5242ef80c916158b
D3 sziklai_pair_amplifier 7576×1077615152, 32328 663.4 kB1514e3d5b0ac51373011c97695b25e67929dfb8323676c09ae71aea1f8e1de76
D4 two_stage_cmos_opamp_with_frequency_compensation 7576×1077622728, 32328 662.2 kBba590a372c056b7d465a17b422c3692314112854c414e4fb948cf38dafd7c4d2
D5 pre-trained_neural_network_for_mnist 7576×1077630304, 32328 721.4 kBb9c4f374c80ddb3c687b217fb1a5eb72de9c0145e0d100ebd8568f5d55b6a9dc
D6 rotfpga 7576×1077637880, 32328 723.3 kBfe0916c201f2c02a6111f592c7acaf875224a098c7089c5e1371e08c772a5f27
D7 treepram 7976×1077645456, 32328 733.8 kB549f2f1b1ffebbe7289df5ef47ddf00a91d518ff579b04b46385b89d1a498715
E1 treepram-red 7576×107760, 43104 717.3 kB1f7cd0b493ad6e8847c8f9af5b2488ce7e6c773f3608bb9a9683fce3a54ceb94
E2 caravel_jacaranda-8 7576×107767576, 43104 721.7 kB6f46c3b7f701bdd7b4cf93ac3dc8336043171d8b6fb365b27f97640002c3e2d2
E3 sudoku_accelerator 7576×1077615152, 43104 721.8 kBe07048f3774bcf228bd7d9ea364056ab4d1f22b12490e419b93a6c28daaf92fb
E4 fixed2float_converter 7576×1077622728, 43104 721.9 kBbe59510e01c277f96180b2d123a72145657183b279d5fa070be695b71df23834
E5 high_speed_adder 7576×1077630304, 43104 721.6 kBe4c766207aa9ab1c1e241ab0f046950444216a29c3d5aea8dd852777148c9ae9
E6 my_proj 7576×1077637880, 43104 721.8 kB9350e4c2623ea73c7f8587a9220e334814c6fda58cde33e8860c6e2a8df9b9f3
E7 pwm_test 7976×1077645456, 43104 736.6 kBf027bbfb56dfb38ca5de9f02ec2749de78d66ec46e886fc2b1cb9f1263c322dc
F1 elpis-light-mpw3 7576×111760, 53880 722.8 kB5bf88f07d5f16eaf8aa9dce11328b3d70d50725ca53696b0221446345ddf186d
F2 vsdbabysoc 7576×111767576, 53880 723.0 kB1a72e1793231a58adfc983c9b2a4576ef8b5c18dc585ada8d47fc4bb1f49ee8e
F3 vsdmemsoc 7576×1117615152, 53880 725.0 kB316d26cd1cf978eb2b4cd726df80cf4c7392cf2a65c5b4b586b0558b8debfa03
F4 caravel_sram_test 7576×1117622728, 53880 725.9 kB7df6fa3226f668bbe3959af38b923b23182270b4615114acefe94c787dd61097
F5 8-bit_sar-adc_with_offset_calibration 7576×1117630304, 53880 670.3 kBa71c3f7ac3a26c2a9dbdb87389eb4f1ae21e187fcbe327124a2e8e46f87f1525
F6 caravel_hyperram_driver_and_openram 7576×1117637880, 53880 726.2 kB6a6d1f9b5d3abc6e2247d16253a655613fb5773d4ae0dd3ced51faf65785b6c2
F7 caravel 7976×1117645456, 53880 741.6 kBc5174a00fe06298a8068c4c2a8f30f6f5e1e6813e91799e1b9bb43039a2ac826

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 VIM4 on mpw-003

Resolved: reticle 5CS8008AC, run mpw-003, mask VIM4

Mask layer
VIM4 — Via4
Process step
159 — Via pad mask
Drawn layer
71:44
Layer on the mask-layer GDS
58:0
Also
Via 4 (M4→M5)
Used in SKY130
yes

mpw-003 — SKY130 MPW-3

Foundry product
EF MPW#3
Reticle set
5CS8008AC
Run date
2021-11-15
Submissions closed
2021-11-15
Projects
53
Fab lot
4206521
Identification
confirmed — Lot records: EF MPW#3, lot 4206521 = 'SKY130 MPW 3'; confirmed by a photo of the MPW-3 mask set's VIM2 plate label (DEVICE 5CS8008A-A, LAYER VIM2 560A 03-01, archived 2022-05-13), seen 2026-08-28
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-3 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-003/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.