mpw-006 / VIM2 Via 2-PLM

the VIM2 shapes of all of mpw-006

40 of 40 dies rendered.

36,377,690 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 (32.5 MB in total, largest 1.4 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-006_VIM2_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-006_VIM2_reticle.png
the stitched reticle, full resolution
20.8 MB 09a5acd64f2556fece105421dc8d07a04eeb77c3893b11dafcf3c4ca84386ef62bd399c4 aa6319d0a041127692f00c24e3f7b321e6ec323196ca17fc9627084fc80985c8
mpw-006_VIM2_reticle_overview.png
the same image scaled to fit 4096 px
726.9 kB 779eddf5d04e317c401b9f1c14d97a9284afbd34ba16fe38e4f7e9763a2323d4f04bbe37 e4ea48e5774bfa0797757bf20d571eac4d84e619a958200442c068669ee5b008
mpw-006_VIM2_tiles.json
where every tile belongs, and its checksum
13.6 kB 058ebc643944a41f5a51fe93bc0b09a2304de5903b29078a016b40795f6d20617f985502 592e30b208898ac86767fcf2d110a0b335b15cc5cb131605e6466dfc68498c8a
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 free_and_open_source_silicon_implementation_of_aes 7576×107760, 0 716.8 kBb14b660876cd05c712bf09bab7eb7d06cafd340c407e0418c594371244aa602b
A2 microwatt_mpw6 7576×107767576, 0 1.4 MB891c8133252d3bc1fb00957b58f9baecf5155c5ecb163fa52f4a07ca81feeea3
A3 hack_soc_-_mpw-6 7576×1077615152, 0 695.7 kB5847effb62f9e6d4fdf26a446026149fbdc279fa38a61eb3a2885905bd4bf2c0
A4 riscduino-dcore_d3_ 7576×1077622728, 0 1.0 MB07a67fa7996a41943ca3393ba1218d7bb9db10f8944cd0670709431ff5ed90fc
A5 riscduino-qcore_q2_ 7576×1077630304, 0 1.2 MB6c57bedbff30feb2cf61e8831061eed3ce9a3a64c7b3cd19ce8568ee2f8e2627
A6 riscduino-score-s4-2 7576×1077637880, 0 965.1 kB79ebfe7ac6e170b9ed378b0a6a924bd731ccb20624d6712578b4169b234c0b80
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 828.0 kB384615f62ad169e6f3e51b82c0f3f453a624d9386dadf3012f895b677ee874d9
B2 ft8_receiver_test 7576×107767576, 10776 658.8 kB66d0dc92d1200b776df588faf2845eaee4fa991005f3b301c600c6ebde31319e
B3 azadi_iii_dft 7576×1077615152, 10776 973.1 kB9426023c000a3d50198043cc6462a785e403a1c35cb9e2df5bf7e158e79e7e04
B4 sramtestvehiclesequel 7576×1077622728, 10776 657.1 kB07305761b04e4274413414c74eb8e8622fc83228bd9295b3e340c88464385b98
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 729.4 kBe4b757f24984242ab8ca77420c0d9a93fa13cd4aee9ca1d15f044c2d3634e7f9
B6 asicle-ro 7576×1077637880, 10776 978.0 kB0295b6e54e5542c4b2cf3007350904a46321bdf2a99576c4502935aa30e40432
B7 10b_adc_and_analog_support 7976×1077645456, 10776 677.3 kBbc43c023693939be39313b9f115a88a883e16a5ea9c049b267930adf72b0f2fe
C1 yonga-modbus_controller 7576×107760, 21552 727.1 kBc1548e1a31e37b270deb77c85746bfe712fa868679c51fbdc91df21cc8a21434
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 717.4 kB1cec2473bf38d7fdb466bc1fbf1190c2eceb6b65386d6eb69a83b8f1fc0d1944
C3 openram_test_design 7576×1077615152, 21552 793.8 kB3e7606ad0b3251982c21868bc9a15e16a63c6eaca9832ff1e5b9f82c9aa3d813
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 726.8 kB53e09ed058f2cefc9f09294e6e7521af110c3cedcb3f592768236640601d0b97
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 706.6 kBb1eafe6d8df632ed64ac1f4b3b809a561d5577f1d2bb1e9075121bc557249e58
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 735.1 kBc0e4b7f23cf11bdca8c1d850bd72276252361e4f7abe9845b5416a9a6b7abff3
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 654.5 kB812d057a5721e7076e4074accd2fb2d14e682b3f24442ded3d92b393fd17ee95
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 654.1 kB69f8e588f368cf9f520ff7ca4b4b7cf7e7294ed8e25eded117e44e93e25b2250
D3 order_prga_mpw6 7576×1077615152, 32328 878.7 kBda034593ce398a022b6da5bf7899f541d336089b1d97783093eda07a3c329959
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 719.8 kB57114fc0a1e5c2625d2906aa90826260d8861608ce197cac4172aedf4f1be574
D5 large_memory_micro 7576×1077630304, 32328 960.1 kB0d4ee4ed79c5c54751277c3d8c446b16669b1acf6e5e40f9ac3130010bfe818b
D6 rng_chaos_scroll 7576×1077637880, 32328 712.0 kBd31ca349fa7dce5a48b3d1e105c8397f386ffa99d1e6eaa42c0cdf1b1dc429ca
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 666.3 kB4bb4fb665d74142507b9166ae2a58a4fe8075c27d85ea2ca2d843acad5a3e9ff
E1 mixed_signal_circuits_v2 7576×107760, 43104 653.8 kBed0d9c87b1bc6b55bb12970a202ae74cec91de9ca448bef4599a991c4b61b596
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 653.5 kBf685ad2f8d276546bb8090e605632f1ad983e62f4bffd4b563e07ba29371c5d8
E3 floating_point_halfprecision 7576×1077615152, 43104 732.8 kB7e5200be16f7f998fa2c85748bf87c28e7346687d69801100eef2f7310d26088
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 725.1 kB9d9328b17073ed0e9038878813d19f6b1c7023df4c6d23fbac7b98158abdca3c
E5 floating_point_unit_single_precision 7576×1077630304, 43104 748.2 kB12f95a98e1fcf5007d771e180c9ee86744e3ea0bb800577583b9f73714a00568
E6 experiar_soc 7576×1077637880, 43104 986.8 kB3e8b4acf437be2398ab8786b6d28f50cc42e0dd4d730df4bb6a7dd9202731345
E7 my_caravel_analog_project 7976×1077645456, 43104 668.3 kBc262161567808d97295660c6a3942127a4a9763af7bd7d38a79762290131aa3e
F1 efabless_mpw6_riscduino 7576×111760, 53880 1.1 MBfe83f447c3692f5933bf3227f949f794a96ac182f63c88da2e5b78855d840e55
F2 motius_pong 7576×111767576, 53880 706.9 kB9863e505b556543ec4a17031af6f504448f058650100d2759f30c02245e24e86
F3 soc_now 7576×1117615152, 53880 747.1 kB454755d28092778fa0292da9fa3b76f3c9d27247e2a1020c70e3f1ee51226ffe
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 882.8 kB9f7562fe6666cc7f352d36475a17959006d2524e09d4c990b180b3d0bf8e8faa
F5 optimised_strong_arm_latch 7576×1117630304, 53880 658.1 kBf734dc63d205339e18426cd7ad2a4d006d2e0cc1a9dd3157d08dc9198381cf65
F6 riscduino_qcore_folk 7576×1117637880, 53880 1.2 MBfea3a4cc2868998749db42c588a10351d6b4b8299b5d11a1cf8a145d6993df25
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 703.0 kBe5e172e5b7cde37152496d3d3855edafad3a7bc8f960bfc05618e100efc0990f

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 VIM2 on mpw-006

Resolved: reticle 5CS8014AC, run mpw-006, mask VIM2

Mask layer
VIM2 — Via 2-PLM
Process step
129 — Via2 mask
Drawn layer
69:44
Layer on the mask-layer GDS
44:0
Variants
Via 2-TNV, Via 2-S8TM, Via 2-PLM
Also
Via 2 (M2→M3)
Used in SKY130
yes

mpw-006 — SKY130 MPW-6

Foundry product
EF MPW#6 (+ 'With ReRAM' split lot)
Reticle set
5CS8014AC
Run date
2022-04-11
Submissions closed
2022-06-08
Projects
85
Fab lot
Identification
confirmed — Lot records: EF MPW#6 ('Held pre-mask' in late 2022; MPW-6 taped out 2022-12)
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-6 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-006/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.