mpw-006 / VIM Via

the VIM shapes of all of mpw-006

40 of 40 dies rendered.

71,376,216 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 (85.9 MB in total, largest 4.0 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-006_VIM_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_VIM_reticle.png
the stitched reticle, full resolution
45.9 MB 17f15fe262c61bfdd102b354236118ecfd4f93489d0be98804a2e38dcd2b87599380a990 30647f3e37ee82953e005aa303397b5fee4c17bac389f01cd6dfd5626b2f932f
mpw-006_VIM_reticle_overview.png
the same image scaled to fit 4096 px
905.1 kB 915c3b9fa55f13aa56405addb905f1b410b1351866b6e270a82a731f0310ab5bfb1e75b2 1389f5855af5035beeb09d718101aa177a6a8d06f91282397ef60f7620d3fae5
mpw-006_VIM_tiles.json
where every tile belongs, and its checksum
13.6 kB aad12892de276354d38e4c0f35d9bd2fd84fc7885a93aa6aa41b918a9d55077ede49ac59 436ca3b1bd1f9541a832d594fd4f4eb264e17f0410f237a07a7d23021820d76c
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 1.8 MB9f340d01a82f12d7e6749ad609acdcff39d730ea43ee98dcabed86be10e2c6e1
A2 microwatt_mpw6 7576×107767576, 0 4.0 MB3f11d1661103fb5406e67b4bfe54cb50c1ef5626dc6f8cba12828589ff55af47
A3 hack_soc_-_mpw-6 7576×1077615152, 0 1.7 MB1af49e32ffe7ce6f0a5447a1ef3d8e00e3bc44fd0909448f6f649ba47246f115
A4 riscduino-dcore_d3_ 7576×1077622728, 0 3.2 MBd669100f02e423c194eb5d56177ddcedfa225ff4549a63ccd2ffd1dc7db1e0bb
A5 riscduino-qcore_q2_ 7576×1077630304, 0 3.7 MBb8130faf65a927e6e428aaf6c55e88c3709c25eec913950a060c88b58860ea27
A6 riscduino-score-s4-2 7576×1077637880, 0 2.9 MB37ca86861e90bda0ec064f7d84aee530e186117b45dc6b61c33527806c9f6c8d
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 2.4 MB8a8eabec2f81827cbb8fd9c8225984d28cc8ea6439b8503d2dcfb94f0bb6a832
B2 ft8_receiver_test 7576×107767576, 10776 1.6 MBdd172dca8666cab1d0d6846ecedb5cd2158f5941e8db5b687f1058090baf90d1
B3 azadi_iii_dft 7576×1077615152, 10776 1.8 MB1c860020557daf3e47aabd0d17f2f43f395fb87cf0a28a0534a59d8fbf441c28
B4 sramtestvehiclesequel 7576×1077622728, 10776 1.6 MBc7f5fb7b0e18f776e18b9ac7ac1ea0c29baa2de8f384d7c32d00230f12fbabda
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 1.7 MB85130cca9814e7ad62f01329e4a5864b817fd154e8036e07d6d0461ecf06676d
B6 asicle-ro 7576×1077637880, 10776 2.6 MB71154a4be98b39e15f980f72eb6603d54e3bc52212fc9fc15610dd1debfa5033
B7 10b_adc_and_analog_support 7976×1077645456, 10776 1.6 MBdf044b6dbc1e4f85586cbfddd7c2aac088b642a5d02bef2d2a042ed5d89234d8
C1 yonga-modbus_controller 7576×107760, 21552 1.8 MB61540c0b9dd4a54927219de8dd964764d633b0d6dcd5ceaf5a3d4a9bf2f3d72d
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 1.8 MB5071a02ef5acd5e469b478c829e0cdc1fd075853cd59bbd1c859e48b86f88fcc
C3 openram_test_design 7576×1077615152, 21552 1.8 MB002f0d8055720ceaa402c099635649e327a3897a9f545779bb722e0a56eda60c
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 1.8 MB5b3628b4dff0d619e5a63f8462f50b5748f8bf7146b5baa0a007185f9c1a7354
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 1.7 MB633c09b011f2f3e393d248cc745e0a208efdc4ec873dbd4980b2aa6453e3009f
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 2.0 MBa3cb35211b42279a6b561dbc3f5c8636783a7a6b15d2898af04b806a53ecdc06
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 1.6 MBb99ac334c7d9bd087c8b2073165bb99042d6b2c185f23fe9aabfbd76e41a6bfc
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 1.6 MB6452eabeb4a9c9bd0ea8638532d374850c184bb71df3ac3f488db5dc5503f21a
D3 order_prga_mpw6 7576×1077615152, 32328 3.4 MBfbebc6de7d7f22512b125f6125387336dd07a15d032fbb6a5e2a873021a9cc01
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 1.7 MB570113c44137613c3b5128ef49b2d418037f0a2e53be8a1da25f8404fc10a1c8
D5 large_memory_micro 7576×1077630304, 32328 3.0 MB6142ac6b378a7ea170ebd836ce6555e292ff8e3f3ace264fbe8e8a7abb62706f
D6 rng_chaos_scroll 7576×1077637880, 32328 1.7 MBd60e944110936c925dd75620d7036375a6776e4003255fc4a8af483bdc9489c6
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 1.6 MBa1dd0384e127de50883e38ccd176f3576eff931dfcdf8dbc0614aed94931f315
E1 mixed_signal_circuits_v2 7576×107760, 43104 1.6 MBcc5c71e4e1117d0037a205c8ed0e9ae0ce4ddae1478647b77ccc18e5b51a6221
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 1.6 MB37112b6b54d98329ec0fed53f97df17c1aa7227f98a2a45ddc87ed2d28420d05
E3 floating_point_halfprecision 7576×1077615152, 43104 1.7 MB1c698c217e13bee4d9f424c8a54ea612ebf39acc5a8028f9d6a12f54fb9e8b82
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 1.7 MB52569bc42bb794d1f16bc0bacacb3e98b3388de5302a961f063ea1269c22f4e4
E5 floating_point_unit_single_precision 7576×1077630304, 43104 1.7 MBc48f130b4c0c0740f0751d4207e4bee6b1cd6d54bfc87f8e40eb999bb0fca130
E6 experiar_soc 7576×1077637880, 43104 2.6 MB3cf80efc51e14aa7834358cce1f4b0f0a38ce9ee9fd2916a10199e592f2e2d8a
E7 my_caravel_analog_project 7976×1077645456, 43104 1.6 MB8906122f995f60d17a437a08585bebd55e03b10a16d5f2925146f485fb1c66dd
F1 efabless_mpw6_riscduino 7576×111760, 53880 3.8 MBb181ff0e87ade127dfecfa8f21e7b35b94d34e27cd776fdd4287711f8aeb2fd7
F2 motius_pong 7576×111767576, 53880 1.7 MB4350ad5dabf4e402a2c807858b937dd1dea5a608b1af93637191f7e174b9e25d
F3 soc_now 7576×1117615152, 53880 1.7 MB36bcf86e66a954b6b22f75b407c18b01c70f35d8f66922f8258973a99ac1d8f6
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 3.4 MBd61a609bb2159c7ff5af3efb6af7e9f51de3ef538c6e5cbdda45528732b60c47
F5 optimised_strong_arm_latch 7576×1117630304, 53880 1.6 MB251fd0ad4dd59c93ff2480009e12526d5cf0c4471a3e69f2ebdf17c6b46df40b
F6 riscduino_qcore_folk 7576×1117637880, 53880 3.5 MBacb4719b5a4ff3a36339b8f43f1370464cfeff30cd25ca9d68e3b497aec9cedc
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 1.7 MB908075d2d0d272b1a0e8253ad4f0b2479ee9f0ad6e3d200ad85b742c8c70f647

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 VIM on mpw-006

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

Mask layer
VIM — Via
Process step
118 — Via1 mask
Drawn layer
68:44
Layer on the mask-layer GDS
40:0
Detail
in the sky130B RRAM tier this is cviam, the lower half of the split via1; the upper half is VIMC (r1v)
Also
Via 1 (M1→M2)
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.