mpw-006 / CTM1 Contact

the CTM1 shapes of all of mpw-006

40 of 40 dies rendered.

426,090,868 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 (157.8 MB in total, largest 7.3 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_CTM1_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_CTM1_reticle.png
the stitched reticle, full resolution
115.9 MB d6bc7773b0687370181efbafacba4c89ecd2784428fbbb51eea14b7d5a3c168eb8ddbb69 9022adbcb1be3830b264391fcbebf02505395a948c1428986c11d42b7554d8c5
mpw-006_CTM1_reticle_overview.png
the same image scaled to fit 4096 px
1.7 MB 294646870a91f9398331df06fbe586d93abdbf23bc800773ea51186f03f2c6e1b5618a2e cee3116ed78c514d180d8afa054c48911bffe5ad2caca5f5474e3c6f15ab4db1
mpw-006_CTM1_tiles.json
where every tile belongs, and its checksum
13.7 kB 3a58d3dcfce521a6ad4972c0d53475351d2fdbea4beb1178830b932dec67ce786f53f17e ae9c4942a0e65c83eb5b06f63aac7bf0d8296a8187e583389088ddc47d7f46cf
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 3.1 MB53bd7285d540ae2b5793aa25a2dbc3f8b1263a23831a93d71e328d0fa94bcf0f
A2 microwatt_mpw6 7576×107767576, 0 7.3 MB341e7785c8456ac5d012dd9d002554dcdc61dd5797e343f59134e5d816ce56ea
A3 hack_soc_-_mpw-6 7576×1077615152, 0 3.0 MB9bdf4784af382e0531a104eff30f786f49209e4dd8dceb4ea34b773ec874ed93
A4 riscduino-dcore_d3_ 7576×1077622728, 0 5.8 MB973f3bffda28b17cd5f0ddba84278dd8eda69784cc71dfaaced2b2f097362d57
A5 riscduino-qcore_q2_ 7576×1077630304, 0 6.7 MB67197c3cbe920a4178e99b7380f54f0ed3adf53d509996add2c22e36ae2e6c24
A6 riscduino-score-s4-2 7576×1077637880, 0 5.3 MB0f76e60aedd31c0690cbbc5810820e4e4acb72c95bd1deb541d6b6cd215d1c85
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 4.8 MB51ef581ef649af3b33bbcbc8032fdeca1e7d8f4b009086fa344a9f95065ae1de
B2 ft8_receiver_test 7576×107767576, 10776 2.8 MBb076960fc229b157b870a978515704cb9cd8ba45e9a682d82565bbc2b224ab2e
B3 azadi_iii_dft 7576×1077615152, 10776 4.0 MBae4042986dfd7ac7ca8b5f86c06c45913e91f511a751d7df5dbd207ec5157bb1
B4 sramtestvehiclesequel 7576×1077622728, 10776 2.9 MB231b1ba30c2b8964a6ef9e43f14a6f191c800c8d289a1d184e151537a6188f8a
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 3.0 MB360b059ca246799ce22a0167088d61ab3ea5d75485722912083f85fd93f7ea23
B6 asicle-ro 7576×1077637880, 10776 4.4 MB0e4c2892e83145a97ec9a35cb559116dd50ce052c463fd8e34aff04692c1db38
B7 10b_adc_and_analog_support 7976×1077645456, 10776 2.8 MB372612d24dcbca8e4eb6498f02118cdbeeaf4feaae21858a4dd7ea233fdab26d
C1 yonga-modbus_controller 7576×107760, 21552 3.1 MBcd002cb2f9e4db375e1eea616619a44433a9db3693418da3e9903266331c97ab
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 3.3 MB51cc470d3fed1da378997f9ae2041fc2763f8a9b3315ca7c650a407de2f65af7
C3 openram_test_design 7576×1077615152, 21552 3.7 MBc58f79caee8e6503a633ec804564dd1d1d1113b0604b1e80ee6a373030bf037f
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 3.5 MBf788de4c5f3032fde51efe8d6607406aa91b0b804a034cf6d18ce9a9542764c0
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 3.1 MB2afee76c9f908eb5ad7aa9b84f5b9bfca24e7ae03ed425382fec0c690b5474a6
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 3.7 MB81a7a08d59f1123b03ec9d92f53b26ffa7a51596af367321973a562425e3d731
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 2.8 MB7d0b10d9bc457acf92720ac19b390aa0e44da9a4ab5a2d7c350975313ad451c1
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 2.7 MBbe4d4028bfe4af25a89b7e7b30fc8c6d8e1d1cdfe8f965b6f703486e0770bb32
D3 order_prga_mpw6 7576×1077615152, 32328 6.6 MB6ba88215dd7df44dd590b7ccd4475ecad6258a1f8135da4ec352ab00098f2b9e
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 3.1 MB4d5b94e14b831c7b1645e8acdafc6dc64b68645689e0e0a91a267ca334a5b6b3
D5 large_memory_micro 7576×1077630304, 32328 5.5 MBc4e179cd0fe083d3d709d752f9f5aea7c0e9f1b514100f8b2bc36491627f4c42
D6 rng_chaos_scroll 7576×1077637880, 32328 3.3 MB1710710a312456ac96cc07a88d4d0399dfcb8d33e62657828a09ce71db6610d9
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 2.8 MB997df7d48740daf8d75ecc9338c83d80d6c6cd4cc7cb9c8d079ee9baf518b659
E1 mixed_signal_circuits_v2 7576×107760, 43104 2.8 MBdda16fccee13d4fbabd72a539eb509bc920b0c92a4543b4446852d336fc775a2
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 2.8 MBd4196285b524d8966277c596db04d8ba66a300d8d4cb4400380d6443cda45851
E3 floating_point_halfprecision 7576×1077615152, 43104 3.1 MBea31de12ccf04d7b6c10d53c3c8fec9a09df61cb613e4e2b7ecfc5c2b0e72ef6
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 3.1 MB582a3d0ef893ac975aef7b19565d938da8d30bade4dfe2348b90090cf3486557
E5 floating_point_unit_single_precision 7576×1077630304, 43104 3.3 MB71e792c0daf90bdf683ce0f66ab538933301eaad3d4af90c5e5decc354526eaf
E6 experiar_soc 7576×1077637880, 43104 4.7 MBae5f6d44723975c9abe834b7411c289e64220e3a45207b6a57964a43d19fd80d
E7 my_caravel_analog_project 7976×1077645456, 43104 2.8 MB72930591ac14ed3086c96c181896f720d2546b5a03eab221848458c99b32bb9e
F1 efabless_mpw6_riscduino 7576×111760, 53880 6.9 MB7a7b610ba410f180d413417bdd5a621e59a06ca74fe9d3656cd9ab856091f759
F2 motius_pong 7576×111767576, 53880 3.0 MB8f6b90a0f0fd96b0fdfee66a5692a4764ce2423bd064bd97d823403dd91738e4
F3 soc_now 7576×1117615152, 53880 3.1 MB1fe971f60172d7018656f7551f9a65e023bd440a73e2eb6d4f2331c316e9bd4f
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 6.6 MBc2df418e202b7b55a596e3eb98d211ac29f9b93bb940c86d5553a01f58065d9f
F5 optimised_strong_arm_latch 7576×1117630304, 53880 2.8 MB6f71ecb8500d9575370b111bc0f13ea6f0505126fc334c65ce908425f4d212c0
F6 riscduino_qcore_folk 7576×1117637880, 53880 6.5 MBffad9116ea4556112e6df34aa1b494e28bcc08fe7299218cef2301b8fb2730e6
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 3.0 MB40333eb39c43f497a6187d2cf695afc187058dd4203e76454e5f4552e7f99ea0

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 CTM1 on mpw-006

Resolved: reticle 5CS8014AC, run mpw-006, mask CTM1

Mask layer
CTM1 — Contact
Process step
107 — Metal contact mask
Drawn layer
67:44
Layer on the mask-layer GDS
35:0
Detail
CTM1 = mcon (li1->met1)
Also
Via 1 (LI/M0→M1)
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.