mpw-006 / LI1M Local Intrcnct 1

the LI1M shapes of all of mpw-006

40 of 40 dies rendered.

230,229,044 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 (307.5 MB in total, largest 14.1 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_LI1M_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_LI1M_reticle.png
the stitched reticle, full resolution
234.7 MB a40ddeb7c2c03c95085c04203674b8808d9890ec881dd514ad52b5230ba4342809ca4e51 8c4899d36a2bb117e775bdc0cb711e87879db1a0408466f1dea61298cc77250a
mpw-006_LI1M_reticle_overview.png
the same image scaled to fit 4096 px
5.1 MB bf5bc8f27de9d77d41447f005b7682073b2c97ff1bc7d461d612ba5202fd741b0c7a9758 abb40b0ded09e596283a52a7d3ad1a708b41cdc6e9624fc794d2b63cfa19f5ad
mpw-006_LI1M_tiles.json
where every tile belongs, and its checksum
13.7 kB 32433b3539979ef37fdc1c0fdf3decac82888b108b2ebab2aeb64d575a46d47dded94229 bda9f7aba4b99a7e8dcda166071b7787bd886b440263f9cf144328c2d44bb4fe
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 5.8 MBb3c209b9c5570c231100740fac9012cff85125f63a3a7a90cdfbc8293844f473
A2 microwatt_mpw6 7576×107767576, 0 13.8 MB79e0538647b34d083be525fc2e27859569c3b61af049defe2e9fbe3617a09835
A3 hack_soc_-_mpw-6 7576×1077615152, 0 5.4 MBe79427ff056fd295935ec4507633ca21209164600594da39030a2f8fe56a2ec6
A4 riscduino-dcore_d3_ 7576×1077622728, 0 11.9 MBf9654b8b06c33093c35584a516009bb03f5eebca220a1839d793b5d1dc9af81b
A5 riscduino-qcore_q2_ 7576×1077630304, 0 14.1 MBd2bb25304b6cf525d9b94e7341ef39da994748f1fbeaf25641bc54b840c6ab45
A6 riscduino-score-s4-2 7576×1077637880, 0 10.8 MB6a429429d411ee7b506a5008e56da2d4fae3878d9d8bb237414f1b9d81ffd0d9
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 9.2 MB8564cc5faf41e6a51970e2cd48de441f309c48479e53f48e04dc9e44e7630766
B2 ft8_receiver_test 7576×107767576, 10776 5.1 MBccb4a9776a6876f5472459076061c611dda3f3707109b010a1d49d445814ccd4
B3 azadi_iii_dft 7576×1077615152, 10776 9.2 MB8948aa225d967e4a609f17b92b8c59900860d83d27ccfe583f8ce0b2ab21ca5c
B4 sramtestvehiclesequel 7576×1077622728, 10776 5.5 MB2dd1ffcbefdf8f16fdeb41493e95971c04124f655740b78edd8f8d6c6f75dc8c
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 6.0 MB563279476cb65d1a14428f2d1e642eea9d823588e5bef550c8f83f47cdd75a8d
B6 asicle-ro 7576×1077637880, 10776 8.2 MBaec35c9f62c9161aa59e67300d86ae76202859f2021886dca52b8d6328d1b1ff
B7 10b_adc_and_analog_support 7976×1077645456, 10776 5.2 MBfa939e26f252d65f12c64c7f1608337885a732edd23e06b3307bc9b050d1c9fe
C1 yonga-modbus_controller 7576×107760, 21552 5.9 MBf5ac21051c6b534028295a988cbee94a11e56562fe32314a067a6360543d9e78
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 6.2 MB34a09bfe8686b047f778ba5c8f0aac2bac2a9b54d4c9ac33a35f0dda186a41a4
C3 openram_test_design 7576×1077615152, 21552 7.2 MB6c9230fb54718994d9cee3a1df0dea84f7b7b74309265fd28e980636babd136d
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 6.4 MB5ebc9b8dc618508876979bbc28158f2a3196fb42d7578fa2c57d5b2b62565f66
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 5.7 MB3878f53c65a1fbb62bc4daad11200946f7eaf682f47263a4d35f70cf25696519
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 7.0 MBdc6ed6b66952c57f23d374304931214e2dbe0808b03df9d7d39239b436ed50f2
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 5.1 MB479c9f9268125aa6bfe691d474a37c3f8562a15aee82948e8f35857f39570570
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 5.1 MB496e2839d3dbc2a3539cb100b9527a2c20a1ca363b5179c7a2ff1a44728a0eda
D3 order_prga_mpw6 7576×1077615152, 32328 13.7 MBcb4efc22039fb22eb1a95238c53d04698b0cc4e74afa9bc51ba4cd49b2febd2b
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 5.8 MB7fd451bce3b2e15a11695989ef80bebfb839947351320e07eae81976373e80b0
D5 large_memory_micro 7576×1077630304, 32328 11.6 MB3fdea9e3bc40f518cfec1c5172e4393abb974dd8ff7fdb4d6f083aa3a98b776a
D6 rng_chaos_scroll 7576×1077637880, 32328 5.9 MB482239f1d47184fd8515ab4a6a4b2415d9a7d5d7f725d094ff146b96fed171dd
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 5.1 MBc817cf5f192408097b1d82809dfd77cfac0238d1a2224b1358ff88ed8aef8d6f
E1 mixed_signal_circuits_v2 7576×107760, 43104 5.1 MBcda5e69d213ca497d6476205591456ff192c481916ad1e21e2176ba13c28b127
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 5.1 MB80109545a026694212161c06cd55fe9176ca30a3618e934ecbe9beed9aad4eaf
E3 floating_point_halfprecision 7576×1077615152, 43104 6.2 MB0445d4730699114bbbcbe250ced8755b743959f711d734a23128959689c0253a
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 6.0 MBcfb58cf73a4b66eff61ce3e2d50563afd6c7e8f52bf4d351e1d1930f6aedc671
E5 floating_point_unit_single_precision 7576×1077630304, 43104 6.5 MB825da2f7c4858b88da15e0915a6b8ccf12e71c30e577cf3d568a3c714ebd2ccf
E6 experiar_soc 7576×1077637880, 43104 9.8 MBc477880c30bf6fc553756b4f5aa19ee52cbc2d624576fffc957bb5e0acf299ce
E7 my_caravel_analog_project 7976×1077645456, 43104 5.1 MBec34ce7ddce7310f0fdf935e4e66507d3adff3ccd6ad221c27d3af32b4be7c21
F1 efabless_mpw6_riscduino 7576×111760, 53880 13.3 MB7702459244c3783a9a23a1985f2f88ef5b0c95bea7c8116c6d854e9fe1f4e7d6
F2 motius_pong 7576×111767576, 53880 5.5 MBddf0f2ebed9c413b9cb7e494644d3d33450ba08cfad9cc09f71a56791179c9fb
F3 soc_now 7576×1117615152, 53880 6.1 MBb142353e783078a40fd9897b301f0ce9330f8719c49a21a352020e5266df7c7d
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 13.7 MB3bac37631be016b87929e12201e32f31949e6bfc9277abf217af994cd7192306
F5 optimised_strong_arm_latch 7576×1117630304, 53880 5.1 MB3c9efb9c0e99e03517a3e9c2daeb95f1d10962c4de945539a6a1fc1008ea693b
F6 riscduino_qcore_folk 7576×1117637880, 53880 13.3 MBe38a1d429aa75fdcddbc4c0ff2894e14b921a1961b2a63d39142d5289bd6d095
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 5.4 MB4341309ba583849e86c41a848d6aec28a28c0fba19976e2fbbb7a6fd8299f153

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 LI1M on mpw-006

Resolved: reticle 5CS8014AC, run mpw-006, mask LI1M

Mask layer
LI1M — Local Intrcnct 1
Process step
102 — Local interconnect 1 mask
Drawn layer
67:20
Layer on the mask-layer GDS
56:0
Fill layer
56:28
Also
LI (Metal 0)
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.