mpw-006 / HVNTM High Volt. N-tip

the HVNTM shapes of all of mpw-006

40 of 40 dies rendered.

551,384 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 (9.6 MB in total, largest 244.7 kB), 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_HVNTM_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_HVNTM_reticle.png
the stitched reticle, full resolution
5.2 MB 12bdf95b921b30defed5453e844f35641e5a51f7a9ccb2bd5ffe482e8904a97591911451 05595b77fb78c10704e3431d1514975c2ee477ba6ff387e5a16eb4eadb8f8e79
mpw-006_HVNTM_reticle_overview.png
the same image scaled to fit 4096 px
359.5 kB 7cddc76ff09512c26202bad8d4f2c74a5f0371817339049b06ead759be5fe6632dfa9f1a 17308a63c733c2ef1845bfaef57e3927760fba6633a79093609115b975a73829
mpw-006_HVNTM_tiles.json
where every tile belongs, and its checksum
13.7 kB 31a0896000537399772ceb0c007eb9b39cb5113fecf3a245002948dd384d6dae54c72e4f e30170dea15b63f532da63977c37961ae7da235d07eae9f7a8a44060a1432285
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, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A2 microwatt_mpw6 7576×107767576, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A3 hack_soc_-_mpw-6 7576×1077615152, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A4 riscduino-dcore_d3_ 7576×1077622728, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A5 riscduino-qcore_q2_ 7576×1077630304, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A6 riscduino-score-s4-2 7576×1077637880, 0 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 sonaronchip8 7576×107760, 10776 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
B2 ft8_receiver_test 7576×107767576, 10776 220.4 kB25b450c5809cba5601c3e905b407e822fbeb7ceb7b2a22855788e2a2a1dac4cd
B3 azadi_iii_dft 7576×1077615152, 10776 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
B4 sramtestvehiclesequel 7576×1077622728, 10776 220.4 kB5405b66adea0e627cf3c46a8ffc4d8d0f46ad08f77c660480457e14524708b99
B5 isa_16_bit_microprocessor 7576×1077630304, 10776 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
B6 asicle-ro 7576×1077637880, 10776 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
B7 10b_adc_and_analog_support 7976×1077645456, 10776 225.1 kB233dd87ceb95e1a0e9aa5799767879d8d15f4cd6fed5c49bca0964d2d0c77dda
C1 yonga-modbus_controller 7576×107760, 21552 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
C2 christmastreecontroller__mpw5_rerun_ 7576×107767576, 21552 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
C3 openram_test_design 7576×1077615152, 21552 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
C4 pwm__resubmission_from_mpw-5_ 7576×1077622728, 21552 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 hyperram_interface 7576×1077637880, 21552 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
C7 adaptive_cordic-based_32-point_dct 7976×1077645456, 21552 240.6 kB5d5e4f2138eba6afdcdac07a4a29f84543f581f864e843594654546cede2812d
D1 cmos_cascode_dynamic_comparator 7576×107760, 32328 220.4 kB25b450c5809cba5601c3e905b407e822fbeb7ceb7b2a22855788e2a2a1dac4cd
D2 cmos_high_speed_dynamic_comparator 7576×107767576, 32328 220.4 kB25b450c5809cba5601c3e905b407e822fbeb7ceb7b2a22855788e2a2a1dac4cd
D3 order_prga_mpw6 7576×1077615152, 32328 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
D4 temporal_runtime_monitoring_component 7576×1077622728, 32328 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
D5 large_memory_micro 7576×1077630304, 32328 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
D6 rng_chaos_scroll 7576×1077637880, 32328 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
D7 mixed_signal_circuits_mpw6 7976×1077645456, 32328 225.2 kB59ac197318b1029a94145bd83545d95df527e6ba7afa98c1b63e0fb6b05d2309
E1 mixed_signal_circuits_v2 7576×107760, 43104 220.5 kB203b058dabc32c5220889a8ab392ba68472d00e3af40942235c820ba1872732a
E2 direct_conversion_receiver_mpw6 7576×107767576, 43104 220.4 kB25b450c5809cba5601c3e905b407e822fbeb7ceb7b2a22855788e2a2a1dac4cd
E3 floating_point_halfprecision 7576×1077615152, 43104 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
E4 floating_point_unit_bfloat16 7576×1077622728, 43104 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
E5 floating_point_unit_single_precision 7576×1077630304, 43104 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
E6 experiar_soc 7576×1077637880, 43104 236.3 kBfd20ce50fa28a6449f0206c937431f5b7ea7532e382faae1f442969801e94bc2
E7 my_caravel_analog_project 7976×1077645456, 43104 225.1 kBc5f8cab0b53a4b79611e203c25f759cc7d7f89e92e05b6c67eae0608d28f84b5
F1 efabless_mpw6_riscduino 7576×111760, 53880 240.3 kBfd122d7fc0a470a5216c3e2ea1c01c07cc64fd2d27dcb6d60450bc1c0747a617
F2 motius_pong 7576×111767576, 53880 240.3 kBfd122d7fc0a470a5216c3e2ea1c01c07cc64fd2d27dcb6d60450bc1c0747a617
F3 soc_now 7576×1117615152, 53880 240.3 kBfd122d7fc0a470a5216c3e2ea1c01c07cc64fd2d27dcb6d60450bc1c0747a617
F4 ORDER_PRGA_MPW6_v2 7576×1117622728, 53880 240.3 kBfd122d7fc0a470a5216c3e2ea1c01c07cc64fd2d27dcb6d60450bc1c0747a617
F5 optimised_strong_arm_latch 7576×1117630304, 53880 224.4 kBb5a40a09840c3da7cbfe0e811756d8cc205e7ef76cf40c84a447f4d01377d6f7
F6 riscduino_qcore_folk 7576×1117637880, 53880 240.3 kBfd122d7fc0a470a5216c3e2ea1c01c07cc64fd2d27dcb6d60450bc1c0747a617
F7 tensor_calculation_using_nngen 7976×1117645456, 53880 244.7 kB6568eda406f0ddf8e8670bca395669760c37ec349951e361c2004d6ced55c03d

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 HVNTM on mpw-006

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

Mask layer
HVNTM — High Volt. N-tip
Process step
68 — HV N-tip mask formation
Drawn layer
125:20
Derived from drawn layers as
125:20 OR ((65:20 AND 93:44 AND 75:20) NOT 81:2)
Layer on the mask-layer GDS
39:0
Detail
drawn hvntm merged with a created part (ndiff AND hvi, outside areaid.ce); only the drawn part is rendered
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.