mpw-006 / P1M Poly 1

the P1M shapes of all of mpw-006

40 of 40 dies rendered.

207,047,298 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 (351.9 MB in total, largest 13.6 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_P1M_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_P1M_reticle.png
the stitched reticle, full resolution
202.4 MB 6ba018acdd3a6b787cfa9816bd443962eaa5836f808dfb8a144770af1b3aa2d1e090da99 3f2a6bb527a3fdaca135482400c3010d354cdb8466dc5bd9c91f0d7d80ee4fd0
mpw-006_P1M_reticle_overview.png
the same image scaled to fit 4096 px
7.8 MB 6cc4e28f1c43690cd1bfbc4bbf4d1541dc3eb836ba50c6a9ba1b2b2c4536ce677215e83c 06aa9f8cc56eb896e21d4e68b0c59e2b73e039aec87ada3955e6f32d63ff9b90
mpw-006_P1M_tiles.json
where every tile belongs, and its checksum
13.6 kB 7902a15a5c58c31dd2c9f7ac28fa7ebcfede89674e3e20b7b1445879a1cc9f3856f2893e 7e0015b7d7540efaff647e4bf11e51f4ac43fa11807bea7cc9d041c37d2dbe98
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 7.6 MB581a4e330503151def1eb449a8171d48b8ad4c0c1a3c50adb9bcbc2dd1f5c4ee
A2 microwatt_mpw6 7576×107767576, 0 12.7 MB25164bbd1d901cfadab7bc671394956dc6186e678ec9c87936918d3bc6cbcea5
A3 hack_soc_-_mpw-6 7576×1077615152, 0 7.2 MB1e24a6d2e9d8aa900ac04cf5549619dba3f750b47547e567ed5c34fdac8e985b
A4 riscduino-dcore_d3_ 7576×1077622728, 0 11.9 MBd27b91a23317448dcbd621a4bdc910b8b2430cfde2df71171f3994a233b56d8e
A5 riscduino-qcore_q2_ 7576×1077630304, 0 13.6 MBb0bcaf71d8bff05fb500fa3b410af8d6603c1202c1b2189ad035f90686c4a219
A6 riscduino-score-s4-2 7576×1077637880, 0 11.2 MBa0dea5ed7272a64d371b91100e13312a492c7ebe4f8ebea3bb7b3f75cfa0adfa
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 9.4 MB84b3de6125443a4c5c241486706c15963a9cccf48cf433eb7024627e655d382a
B2 ft8_receiver_test 7576×107767576, 10776 7.0 MB8bae8bcb8b48e07e1da2349d36954dad0dd56ffabc860cbc7145f85bce32bc41
B3 azadi_iii_dft 7576×1077615152, 10776 9.7 MBa2f65a02cc8be107b0a2027cf1d446e34662ed68332ec2568b7dc996ba3be5d1
B4 sramtestvehiclesequel 7576×1077622728, 10776 7.2 MB7006fbedabe594b042f170176f12d3d2ccf7bc97bda81ae426e1cdf1fa3bc517
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 7.6 MBe877b206ffff4147a2b81bbfc1a88cefb40639330861306104f5edcc3019bc70
B6 asicle-ro 7576×1077637880, 10776 9.4 MBd77beea29fa7137b9b7b5cc9299cb77af13122b1a90c2b53a720ff6b6270f74b
B7 10b_adc_and_analog_support 7976×1077645456, 10776 7.1 MBe0b113f2f62e7366dc313b8e270e5fab19c8d0e4eb4224bf5e1b452bdfc3c81b
C1 yonga-modbus_controller 7576×107760, 21552 7.6 MB504cb0e4a95f4f2ca8cbe172b533d017930d07fdc230f7e17520f3b81dee3aa9
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 7.9 MBd6a77703f32dd3abaeba83014cb6b1618cff9234f56d4c63d27b3606606d6965
C3 openram_test_design 7576×1077615152, 21552 7.4 MBa28b29d2ec7bd6edf24c8cd8a5832c0053620e16bdd8723d3d01b842704b04ae
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 7.7 MBcf08157f635a6ad52a84ce522b67463924cd3dc4e0083c06f209eef150e9249b
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 7.4 MBe1c0a9b933598d00e9963fe719374fe74baf958158f5879d60efd0fa528821a0
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 8.5 MB9aa244a2b27afe56255beffd162e2d7fad8cd35e2de548318d3f675665c2e77b
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 7.0 MBd3d308ef98c2ac327059e91fce392fab3c89561ae76d4fd28ae9b0876555901a
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 7.0 MB6495cf88f187b3d51f2f9736970230b092e2ddf0337b45c75deba7198c5dc4ba
D3 order_prga_mpw6 7576×1077615152, 32328 13.2 MBe774d64b6e5dc5685ab6cd856c85b84590e58ef3619f76d0136be1b8e0729d9d
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 7.4 MB5fe727e262d42a2fb6af7d646c7c19d780214a2bbaca062812a9e36c0cba2b9e
D5 large_memory_micro 7576×1077630304, 32328 11.5 MB8e7657baf07ca786884fb049421d11f59a69cb07f77a042e156d7f62024c8709
D6 rng_chaos_scroll 7576×1077637880, 32328 7.7 MB91c174cfe32cd0910e8983d975a9a54fb8ed44f036f9d0a5dc3086eb4da98cc8
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 7.0 MB44861a13d722cf3c3cb6a23de150370508a5c3dbb1a7e9ff90ce75e05f6b7a1e
E1 mixed_signal_circuits_v2 7576×107760, 43104 7.0 MB5092eee347543728cfa3135ae7bb1a2c5a3b98afd2969027bb21ee662d92c093
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 7.0 MB6e4405ef8f692b9f53fc5366e0e0645cbd7c1626fb362224714fcd8811b3d015
E3 floating_point_halfprecision 7576×1077615152, 43104 7.7 MB9cbf4ba14e31709ce827264419d3c9d44ee24c4fa35dacd266fc90c9f72b255b
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 7.6 MB16dd44fe4c14bb107526c48465a4d583591bb0242610571a89c4e0680b508b1b
E5 floating_point_unit_single_precision 7576×1077630304, 43104 8.0 MBc469ce4cc782adc2d86d1542e7836275ad678d51b0efbaefad9c2bfabfbcc7d0
E6 experiar_soc 7576×1077637880, 43104 10.6 MB9d81a514e6592717e143d754a014ee827f57b984d2b6e9983b6ebb661584d138
E7 my_caravel_analog_project 7976×1077645456, 43104 7.0 MB8cc5d2f5c3481767533b5f5d9687fe3761c406f2a03689226d800baeae545196
F1 efabless_mpw6_riscduino 7576×111760, 53880 12.9 MB1ce31092a05539f1c25189fa28fabcc11e3052c21df9ebf8fb213cc3e0f42953
F2 motius_pong 7576×111767576, 53880 7.3 MB910be149722b51771dc6b8289d17f149e60c58e81a539c21a6c7be0e6744aeb0
F3 soc_now 7576×1117615152, 53880 7.7 MB9c367365742a6d97beff055c787464486de3dec8b27f50f38501416b17f575ef
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 13.2 MB49ab735ce6e473862324eeae2c8517567f0f8fb02c3cd32a55149e3c5138649c
F5 optimised_strong_arm_latch 7576×1117630304, 53880 7.0 MB90c9db38d01c4d0ecfd5c4244aab01c94935c16a04392ca5b41c434c242c42d8
F6 riscduino_qcore_folk 7576×1117637880, 53880 13.0 MB292644876eb0cd165064e6914e43b259c4ae2e4affd20a810374d534c033d6d8
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 7.2 MBc73d57115acbdc7be21481dce62bab4c92cfc03342574750dae11675a057c18c

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 P1M on mpw-006

Resolved: reticle 5CS8014AC, run mpw-006, mask P1M

Mask layer
P1M — Poly 1
Process step
61 — Poly mask
Drawn layer
66:20
Layer on the mask-layer GDS
28:0
Fill layer
28:28
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.