mpw-007 / NPCM Nitride Poly Cut

the NPCM shapes of all of mpw-007

40 of 40 dies rendered.

26,683,434 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 (108.2 MB in total, largest 5.8 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-007_NPCM_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-007_NPCM_reticle.png
the stitched reticle, full resolution
86.6 MB 55ad4a3d77f6614e959beb438d39410a3456696d3b87cd4a698cadc43d471cabc2c2a951 e01bc8caed44b9f02b82381c88f61df1369af283067f0fac0913b0f4a6e99668
mpw-007_NPCM_reticle_overview.png
the same image scaled to fit 4096 px
2.7 MB e1d7b07c0a87f55e5c0aca9b5a13078ebb495e1603065e7569acaf803fbca8f88d1041cf e07434c4cf030a43103ab80f9b727146cc33e0e6207695fdc0c046a6faddebdc
mpw-007_NPCM_tiles.json
where every tile belongs, and its checksum
13.6 kB 57125305f9c2af1f4b17d8f7b0fd908bc0bb64835001eea7a5f6f5e17eb0ce6db8418fe4 da9ed99811aa62f32b5aa9fbdeae2af0f14a03c5f21ac7199179cf0351a91241
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 tinytapeout 7576×107760, 0 2.1 MBd46735cd97e2c70890467a124171736aebc8e8d60105c8d504393d63dab6c8a7
A2 zero_to_asic_course_group_submission_mpw7 7576×107767576, 0 2.7 MB06320c60a2234960213711422d6f7a06b8dc6f6519fcf75cc65ef400844d92d4
A3 microwatt_mpw7 7576×1077615152, 0 4.2 MB80780b8265a28eed43c756c564d9f6e096e8412c5b5945209cb99222433eaab2
A4 yonga-can_controller 7576×1077622728, 0 1.7 MBd4793fb24a22972d999222a9d1679dafc9ae37394a24d53c9c5bfa22f21937b6
A5 rocketalpha 7576×1077630304, 0 4.2 MB13544d5bef72737a809337c4395d93ae030503a45d008fb34b176a1eab942c0a
A6 riscduino-dcore_d3_3 7576×1077637880, 0 4.7 MB5ca073f80b1c8cd2477f5167beae4f2a63d9567506762ba4b7f5674e13a438d2
A7 SkyWater test structures 7976×1077645456, 0 106.8 kB56c5b78f9b86a53fdb64304acc12fba53d045b0526cc20ac1552594029f8a19a
B1 riscduino-qcore_q2_3 7576×107760, 10776 4.7 MB93370a2818bd80974615d97bf16832d0502a3ab4a79ec6848fa0c1b7e3e8ea15
B2 riscduino-score-s4-3 7576×107767576, 10776 4.5 MBaa70ad586a558aae3e6c22e0d3f1e7ca52115ee32ce5cb737e8e13413380af74
B3 nanofabrication_project_using_openfasoc 7576×1077615152, 10776 1.3 MB0976a9462baaae09248078c0f04fb79368a15ea76846935ba641975798aa9f27
B4 sramtestvehicleg3 7576×1077622728, 10776 1.6 MB05d9d73b6357998d8713323cc465b00ae67a35aee86fca9029ee6ab82e26567a
B5 analog_frontend_for_particle_detection_resubm 7576×1077630304, 10776 1.5 MB9aaf491705e45ec78c87c7f190fcd422b852baba0fbc1727bbb66fce02669676
B6 isa_16-bit_microprocessor 7576×1077637880, 10776 1.8 MB15f8fe0c104774bff2de7902c6f853e9c2a12064ab81f7524d671a2cc718dc01
B7 reram_crossbar 7976×1077645456, 10776 1.7 MB64d2d62fcc80d637227b7a32de3a93d214b7602073bcb26cdb70bae823536a58
C1 trainable-nn 7576×107760, 21552 3.0 MBc9fae1a20a3d91c051e8b4d9c523289a6a9f415d94fdd0e795086ca0cb23f207
C2 10b_adc_and_analog_support_-_update 7576×107767576, 21552 1.5 MB728859cf17047028431afd0ac46aca41fa77d37b3c03554f805ece825b39086b
C3 bitcoin_mining_asics 7576×1077615152, 21552 1.8 MB3db7d97683f81127e807858d193604491a6496a4681c20694e8695e283a44286
C4 yonga-mcu 7576×1077622728, 21552 3.5 MB8406624f1f2cf4ed62067fc2d805d16fe1abbe79dcbcafef776714c1c139f162
C5 SkyWater test structures 7576×1077630304, 21552 102.7 kB404d2b68827b8f64404c8d26b19179b934888b57260a33a16e25162769e85650
C6 soomrv 7576×1077637880, 21552 5.8 MBdd2af6dfe1e2045eadc09b359a93bd3ac5356943b5159e44625bb586cf8321b8
C7 marmot_risc-v_asic_for_motor_control 7976×1077645456, 21552 3.9 MB5a44be796332b24e0dec2a134b2e5691eb28511d229b490b87e1446323f3892e
D1 mixed_signal_circuits-jun13 7576×107760, 32328 1.5 MB4afc5e5ea07a194f2b41c5c6b6b075a4d8c822ca59918dd901ea97b032cc712c
D2 fpga_programming_management_unit 7576×107767576, 32328 2.9 MB3f31d5bacf7d6a7829d710a166f1de9e6f84a0f641b006d5cffac6d66c249ee7
D3 warp-v 7576×1077615152, 32328 2.0 MB9582291ca200dfcdc35c4ea4d848ce0689f262347eb96cd86e213cddbc053feb
D4 leaf__mpw7_ 7576×1077622728, 32328 2.4 MBc0060df78c04fc9531ae81d5d0440842e846be6a3b3d1019acd154ae920a3325
D5 in_memory_computing_sram 7576×1077630304, 32328 1.9 MBb34442470249866a984dabfa3b8894746cf6324664d893186ffb399763121657
D6 rng_based_on_a_figaro_oscillator 7576×1077637880, 32328 1.6 MB46598b3a4a45872bc0f57f74ac45f4ff7839ccbd472b3bd063bf1a2b0f67f29a
D7 reram-controller-mpw7_v2 7976×1077645456, 32328 1.6 MB7e1575e8d59b92ec0a952cc5cd30960d94eb9930bc35efd3dcb3b91ba439bc1a
E1 enhanced_chaotic_oscillator_design 7576×107760, 43104 1.7 MBfda00cc8b4b59d6e499d0aad0aa9652348e3a251512173f023a967a9ee512b26
E2 in_memory_computing_rram 7576×107767576, 43104 1.9 MB794b2f640ac92a6582d5ec70d3a10c809463750535f9b7c7c8bd4ee912067065
E3 rram_imc_v2_flat 7576×1077615152, 43104 1.9 MB794b2f640ac92a6582d5ec70d3a10c809463750535f9b7c7c8bd4ee912067065
E4 topmetalse-dps 7576×1077622728, 43104 1.5 MB07c3f5be27f8cf2b3fe77003618fdeef08b2e32d45e6d5d84a29a4f382d4b727
E5 chaos_automaton 7576×1077630304, 43104 5.8 MB6bf24873bae1ceb6d2cc17c85208e91423aecb8a97d1344bcb91f49c84508b5a
E6 hehecore_resubmission 7576×1077637880, 43104 3.2 MB89bc7dee1522ec4e0101c57bae7030ee3cde3ac6993617c279cb1e03605bb3d8
E7 waveform_generator 7976×1077645456, 43104 1.9 MBbe3de05911726d7909654dfb6a97d29de6d983ceec2dfd018d478d03b8a406ca
F1 rift2core 7576×111760, 53880 1.9 MB568f0aacf48a019034f69f39d1fbb0c7a01815d69e1667adaa355e09b1a3fe25
F2 rift2go_2300 7576×111767576, 53880 5.6 MBb450f528ec1883baf96903a0130b92c49d6abdf4fe1499981e3cd2a33aadfda8
F3 sloci_resubmission 7576×1117615152, 53880 1.6 MB6a00625085609c89d63563f2cadfa9a43392e181b7f2d54544405bbd91330e6f
F4 systolic_array_matrix_multiplier 7576×1117622728, 53880 1.7 MBab4b84737ae439fe882b6cb26c1f89486ba1c275f276db2029c58f7cc19c2d9d
F5 crypto_aes128 7576×1117630304, 53880 2.6 MBe83f4bdb9d2a7fa3189c178450a3a39d3e2721ee8d057cd62e914af12ac4e8d1
F6 graphics_controller 7576×1117637880, 53880 2.2 MBdc6821f8149ca0c41d9bc59fc186002f20d4cb645cd3169be8542efa9d4232e6
F7 prga-test 7976×1117645456, 53880 4.3 MB7ece168bc17ea28de1151f03fc326a0415b90f0064c86abc22effabdf26df07d

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 NPCM on mpw-007

Resolved: reticle 5CS8016AC, run mpw-007, mask NPCM

Mask layer
NPCM — Nitride Poly Cut
Process step
78 — Nitride poly cut mask
Drawn layer
95:20
Layer on the mask-layer GDS
49:0
Used in SKY130
yes

mpw-007 — SKY130 MPW-7

Reticle set
5CS8016AC
Run date
2022-07-08
Submissions closed
2022-09-12
Projects
106
Identification
inferred — Sequence after 5CS8014AC=MPW-6 (8018 is the re-made MPW-4 set); packing list 2026-08-25
Shuttle page
archived copy of https://platform.efabless.com/shuttles/MPW-7 — the platform that hosted it is gone
Foundry data
third_party/shuttle/sky130/mpw-007/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.