mpw-006 / INDM Inductor-TLM

the INDM shapes of all of mpw-006

40 of 40 dies rendered.

17,447,407 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 (50.8 MB in total, largest 2.3 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_INDM_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_INDM_reticle.png
the stitched reticle, full resolution
25.9 MB a7eb3210df8e05db11ad2d61536de0e4175e05caa5262dac0d7ce8ff1ff1362ba5ad9421 7b1fc9cb41b511163c371de7d142069c3424f4d545d392934fe6ecfed97ce85c
mpw-006_INDM_reticle_overview.png
the same image scaled to fit 4096 px
2.3 MB 8d6cd8d5eefff986057adab86b0c393074fbf742ab5518e4ce8bb62e928e11388efc2250 b9112da93448afb768ef38a8a2410bf6c79873d7b5eda30f4355cc8c7317b1f2
mpw-006_INDM_tiles.json
where every tile belongs, and its checksum
13.6 kB 76bd4e0be141d93dd10443cff577aa87018106ebe39ac9389261f4d02d708551b6830192 98d04df3a3dd4f603645f93555dc27914cff37045d8ed9e2e5869eeac86205e6
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 1.1 MB557042a7e2e9f97ff74f3a7567e9c74e64ca62a7b105093965e99e1fef6d6996
A2 microwatt_mpw6 7576×107767576, 0 2.3 MB2cf5535d3d89e7b8d7ed0776a002c48c4e25c66386235e3317bd6a601c35d239
A3 hack_soc_-_mpw-6 7576×1077615152, 0 1.0 MB5fbaaac59321aa6a4902091f1cf3cbd459d38a8d9dba9c40855a31a8106b62a7
A4 riscduino-dcore_d3_ 7576×1077622728, 0 1.8 MB9e975b38f74e3c717d7d52950f18af59ca8e53d4e018cd61ae261b6460fc4dd6
A5 riscduino-qcore_q2_ 7576×1077630304, 0 2.1 MB74ff3b490ddec03a681ca80eaa1d41fd7a3e3243ad424e0215df624187e733e3
A6 riscduino-score-s4-2 7576×1077637880, 0 1.6 MB0a2b187a1387f9c5261a025cdc774ac2ebe95d76745b77cf16639bb712ee0300
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 1.2 MB07fb2472024e4cb771cb25b287b4cf4ccebc9977f5b12013d52b677ddc4a7193
B2 ft8_receiver_test 7576×107767576, 10776 976.2 kBc4cb9d973a150f70623980e6a898e69029dc77bc38d5e5053cf2911b55ce5c80
B3 azadi_iii_dft 7576×1077615152, 10776 1.8 MB5196c4e80c24e0281f695c859b8d2a953712b85f41ca433241e7894302caa84f
B4 sramtestvehiclesequel 7576×1077622728, 10776 968.2 kB69544a65b2c6f2f10fa75e349c43dc317fefe71dbb116424fa5b148cf7a609f7
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 1.1 MBeed1537959985f8f349fce5d0677498a5bb5119c70d410f070e33cec1a0868c2
B6 asicle-ro 7576×1077637880, 10776 1.6 MB2997ec1f40997d810e1998d09f77632fe3376c76f215bdfc7c8317f7ab2becbb
B7 10b_adc_and_analog_support 7976×1077645456, 10776 990.5 kB2bbbfa21afb78f9e3bd1d17a92f365630d977503da25518f94355cd2d2b929d6
C1 yonga-modbus_controller 7576×107760, 21552 1.1 MB3d3f95ce7e34f3e7be47c0b8a47da7caacc73a6f3a7564cf53d1c4179a95fa19
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 1.0 MBcde3dfc8df225c53816d7e118ed418cf2f3b942204e781311bf8e07c33b56571
C3 openram_test_design 7576×1077615152, 21552 1.2 MB5eab3e5172c5b4a42f139bd29f497d826372c0c12b4bec0251dc151aaa97ef72
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 1.1 MB45bdea1e0cbba6f8973704712125574bad1e866f3ad0681a66a12fdb97cef774
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 1.0 MBace0135cd6bff6bc05d77b6b012cbdb6bb8a16337c827c6d57100d84b29edbf7
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 1.1 MBbe96da12765b0f6d7fc3fc813d4ef22ddb4375b08474f051c44ef4c5b333367d
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 969.0 kB7f1c9a01253d2a74cf24efff6435a53ba5b04f4babcd9fd6f75d797f8adf3ac7
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 968.3 kB60784005103fe71a152621e1ac89b587f1cc1ead5860c2edaa4e2c8e992b7499
D3 order_prga_mpw6 7576×1077615152, 32328 1.3 MB7e39fc941e8950982a86e002431416325cf49ce38637fe065f599e177ca8600f
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 1.1 MBa07aada5dfcc83c7c4444be168fdcfa1af0c78877628f89c029dd7e41640886e
D5 large_memory_micro 7576×1077630304, 32328 1.7 MBa9016002e648f1f7b498eaa9823516d543d4ec25b80da7f03edb88fc80264809
D6 rng_chaos_scroll 7576×1077637880, 32328 1.0 MBdff480b16d5ffe584c4768e9fcc62d64ee001d61ba75284a7fc540144b87cce2
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 973.6 kBc9d739b1da91d5c40a8cc9087baad1b9a389e4b9864526cc6d7d957c4694e024
E1 mixed_signal_circuits_v2 7576×107760, 43104 966.8 kBda456c0171db6e116d34b41a91315a4f0bcd587c4e5cae5419364ea65a2fd2c8
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 967.2 kB1cb1a7c6215015382630791895c317407e9c45aa54101cee1dfacd91a442c2f6
E3 floating_point_halfprecision 7576×1077615152, 43104 1.1 MB5949614bb7e3297a8897eb63561b018cbc5f964a6d7ebab790d89c1b4776a1a6
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 1.1 MB078b11563d366da9ae3dfc10a44e10d347bb354ae007ef18104f35f30177df81
E5 floating_point_unit_single_precision 7576×1077630304, 43104 1.2 MBe04a134372a8241cc1da8baa091a11de8031b8a4d856151189d3e635ccf02cea
E6 experiar_soc 7576×1077637880, 43104 1.8 MB4e79b9d7b64ca0d3f8701e2230b0b65672eec55a457f6b314c3df59f1ee3393d
E7 my_caravel_analog_project 7976×1077645456, 43104 978.0 kB26f866a2c3f87ebef4bb7ed4a6820a6abdfbb661b56a19448413e76913c3e47e
F1 efabless_mpw6_riscduino 7576×111760, 53880 1.7 MB93ae99de919cd32b3a5952482af6a84add7fd819255d36b195ca7db20fa2ce17
F2 motius_pong 7576×111767576, 53880 1.0 MBa314061384d2140012297d3e8340acfbe7a0da5dfd70545683e260c56e7d1947
F3 soc_now 7576×1117615152, 53880 1.2 MBefbc27b2e4a19349d4e7e50bc0de69e53c0693b202ad200be3d73ae4981064b0
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 1.3 MB1df7c3a8d556d917cbd8e6ea33acc40b91f3481181d4bca36f733287fdc161be
F5 optimised_strong_arm_latch 7576×1117630304, 53880 972.5 kB2bff470cad601f34d0cce27383e3320014a76d48127d04b97601c16377467485
F6 riscduino_qcore_folk 7576×1117637880, 53880 2.1 MB1c9b4ba2e6137ba39473849c6f7bc1b2ed0acd5842ad390526de7578952671d5
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 1.0 MBb1f8ebadcd4bc11b1c93213107785c3246b525c466ea736c3daf41ed993151a7

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 INDM on mpw-006

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

Mask layer
INDM — Inductor-TLM
Drawn layer
70:20
Detail
INDM = met3 (thick-last-metal flow, not SKY130)
Used in SKY130
no

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.