mpw-005 / CTM1 Contact

the CTM1 shapes of all of mpw-005

40 of 40 dies rendered.

361,238,161 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 (130.6 MB in total, largest 7.0 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-005_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-005_CTM1_reticle.png
the stitched reticle, full resolution
76.9 MB fe38bcf6927f09da84f98dd8b66797245a6b529c29344639d6bf8aa968e9a68000ac2f50 6daf0834c555f493b53d88c6f83f578a2ecd6b081f14d8652f2028504801e085
mpw-005_CTM1_reticle_overview.png
the same image scaled to fit 4096 px
1.4 MB 93861fedcdc0d264b303c0817c3f59e9d0fae69f56a75b43c2e0e5710626715a7872339f d5bab13dae4139fbbc549d790d1b614370162c61ef71cb3b32502e9747796834
mpw-005_CTM1_tiles.json
where every tile belongs, and its checksum
13.6 kB 37717f4c4a345f100b3378bb4cf47fb66030db03a4f77113fae8b2ad7418b9b5ca8adf41 d7d5a0929bfee95a2caac03033ad1326fd6b92ab3fd5f079958a5f29f7599e54
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 pll-based_capacitance-to-digital_converter_mpw4 7576×107760, 0 2.4 MBcc4ec5351af1fd8548755c76aa877f05dbfa7a463aa6e14e819a052059ce3bbe
A2 mpw5_cache 7576×107767576, 0 2.6 MB7074d8cbdb3946adb61d3a3163a4d2d829715070e6be6b1194dd5a9030b156a7
A3 zero_to_asic_course_group_submission_mpw5 7576×1077615152, 0 4.0 MB3e66c7e0c87bb4b3133b8c6b25f9d85f2dcb037f9b33296dfa31d66f785e7d65
A4 zero_to_asic_mpw2_rerun_on_mpw5 7576×1077622728, 0 3.2 MBde01f0cf7bad55502def517a1f9c3043b588d943b83925ce7a2964a6a675363d
A5 zero_to_asic_mpw3_rerun_on_mpw5 7576×1077630304, 0 3.1 MBe6ea4ac69c0db1ee0cff65852e6d5819da3af174ff02899e9bce73205c44b895
A6 zero_to_asic_mpw4-rerun 7576×1077637880, 0 3.7 MBd33bc69faf94deaceec5e52426f23f2b2d9df3465eaf31e8ec1b4e683ab85c02
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 actuatorcontroller 7576×107760, 10776 2.7 MB2867a8ce06a8b5d4e30f1c702df67af59adcd8feb09cce3b4f3b5df0b75bff6d
B2 microwatt_mpw5 7576×107767576, 10776 7.0 MBbc780216a4589c19e5f6cb75d8b57b3f2e804e67c1b3b0600e1431f33188daa6
B3 armleo_gpio_mpw5 7576×1077615152, 10776 3.1 MB52060c5ea7cec68914ed5be64a010d38bfb33b864e77a79d6bc3ca3c35bf0f13
B4 fabulous_efpga 7576×1077622728, 10776 5.3 MB320df7ab17b3bed20586f3d1981939ff9359dbcd0526adc649415001b53184ac
B5 i2c_controller 7576×1077630304, 10776 2.6 MB08dc89276cb2ccc0c5a338672d1018784810d842291040b9224bbcebece80166
B6 lbist-mbist 7576×1077637880, 10776 3.6 MB7181b44a77ed6f93119e44ce70d66726ab9dab6b6e94525ead9f9505bf9d35f5
B7 riscduino-dual_core__rd0_ 7976×1077645456, 10776 4.9 MB16b61717a222484eed8cbfa5f84ee889d63771281d1bb2dcfc7c588376048a1d
C1 riscduino-qcore__q0_ 7576×107760, 21552 4.8 MB327ad9562391ca064fe8ef6e224da78746a4fb2706391e09a5edbe63a027d7db
C2 high_speed_vco 7576×107767576, 21552 2.4 MBaa9bb16dc70e5600f3e9bdfa8a5029fd88088e4abcc10b99b16f56f92b3d4207
C3 openfasoc-cryo-gen 7576×1077615152, 21552 2.6 MBe03131c7df69653b3bd3136204935536a6a90270bc4b487480e4b8bf5dfea124
C4 microwave_signal_generator 7576×1077622728, 21552 2.4 MB253a66b8ccef4a9bf9f99585141d7cd2821b1e4bddc4f9525c65356b1039d609
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 pico_design_resubmission_mpw5 7576×1077637880, 21552 3.7 MBb3e60330e6c37c957516de1aa525bb8efbf09ae1b55698e280fbac615d9c55c2
C7 ask_modulator_and_impedance_transformer 7976×1077645456, 21552 2.4 MBb0cf744336abaff93d2743bb66dbe884e9b8abccc18ee7943fd36183c94cdc91
D1 baseband_inductorless_automatic_gain_control 7576×107760, 32328 2.4 MB61cfe69fb95e176931f259aa8b3fd3206c1a7ad212f60f39436a3d18d7374eb4
D2 azadi_iii 7576×107767576, 32328 3.6 MBb9548bad94571a30b972e7aca7ea183e1d653c10a3a333c3a65083bb5e4a9631
D3 tia_for_physic_experiments 7576×1077615152, 32328 2.4 MBb22060c455bf3dfea546fa8aae458c13495b6915fd324e6b4c934a80e4b66047
D4 qf105 7576×1077622728, 32328 4.4 MB371c3cd2fb9e17eda59e1b490a426509fe6413552ca7a01f03888af44721d140
D5 coriolis_test_soc_-_mpw5_vexriscv 7576×1077630304, 32328 3.2 MB16fa2b980cf08b84b1c804ad0fc1f3e77ff6bea6d613db7465e244b9985e2af1
D6 junga_soc_mpw5 7576×1077637880, 32328 3.3 MB02c1ebd78132aa70e115f999428b2ebb5fdea6fb25dd3b637fe5251e03769e9d
D7 nand_flash_mpw-5 7976×1077645456, 32328 2.5 MB3641a7212734f229b1c51255dd9109e19febea5850a88d6f7bf920d534662638
E1 kasirga-c0-mpw-5 7576×107760, 43104 3.4 MB30965282a4e54785ec3ed400ad6b2efd64312f577da89f784109de3cadf2c621
E2 delta-sigma_audio_dac__mpw5_ 7576×107767576, 43104 4.1 MB6ba1416a7f13cbfa935369f3c8dbdd28b54faed4364c7e70cfef07b733d9cdd6
E3 wirelessenergyharvesting 7576×1077615152, 43104 2.4 MB2061b35b160b0a78792fdb95b2ea49f1ce8cd9ca4cfa4c0692707df613441102
E4 caravel_raster_engine 7576×1077622728, 43104 4.9 MBd974e09d4481b3688e5acf1918a8d30ad91765e1e4adf04770ba7ddd96ef8122
E5 DDR3_SSTL_TEST 7576×1077630304, 43104 2.4 MBd01beaeb0dc5429655967df6ce5fa75cfa6cf6d0617443a07a6c5fad71d6effd
E6 accelerated_risc-v_cpus 7576×1077637880, 43104 2.7 MB4987933f331bb81d1d4dca5265a99cf4a99bff63b54fd817bff38434872d89a6
E7 alu 7976×1077645456, 43104 2.6 MB625d1aa3cb25add05d064699daa068a7604afceca598693581bf7f1dc019f84b
F1 4ft4 7576×111760, 53880 3.0 MBd317814ff9f327edc8cee73d5cd53977c912105fdaaf3769983effa748d941cf
F2 rng_chaos 7576×111767576, 53880 2.6 MBe3435b0dd8109c8387336fbb71d6e8364269a11fe6b532c79886c8b142594d4b
F3 uetrv-ecore 7576×1117615152, 53880 3.4 MBd06443992ad33d332bd2d3901e70a194fc0d45562b4ebd5cb93f6ae01c4ef846
F4 systolic_array 7576×1117622728, 53880 2.7 MB0a2de827bebf1ac74bf07f844bd7170dde5a71a2347e317581f81fd95a804c7c
F5 reram_test 7576×1117630304, 53880 2.4 MB8287f0a630bf7f2aab9f4e5d189bf29804ac7a6efcf07c8a14e743eae15fe1a9
F6 secure_memory 7576×1117637880, 53880 2.8 MB55444b4aa358da4bee7707ed1a560d45e357708f54b898ba68dc1e7921d1ecce
F7 asynchronous_fibonacci_counter_testfix 7976×1117645456, 53880 2.6 MB264e0322cfc6be8674d57ec64ed1cd205898fe4056ba692a4c4d0a848ccab09b

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-005

Resolved: reticle 5CS8011AC, run mpw-005, 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-005 — SKY130 MPW-5

Foundry product
EF MPW#5 (+ 'With ReRAM' split lot)
Reticle set
5CS8011AC
Run date
2022-03-21
Submissions closed
2022-03-21
Projects
74
Fab lot
4229389
Identification
confirmed — Lot records: EF MPW#5, lot 4229389 = 'SKY130 MPW 5'
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-5 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-005/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.