Efficient protein structure prediction fromcompact computers to datacenters withOpenFold-TRT

Didi, K.; Sohani, P.; Berressem, F.; Nesterovskiy, A.; Fomitchev, B.; Ohannessian, R.; Elbalkini, M.; Cogan, J.; Costa, A. B.; Vahdat, A.; Kallenborn, F.; Schmidt, B.; Mirdita, M.; Steinegger, M.; Dallago, C.; Chacon, A.

doi:10.64898/2026.03.11.711233

bioRxiv · 10.64898/2026.03.11.711233

Efficient protein structure prediction fromcompact computers to datacenters withOpenFold-TRT

Didi, K.·Sohani, P.·Berressem, F.·Nesterovskiy, A.·Fomitchev, B.·Ohannessian, R.·Elbalkini, M.·Cogan, J.·Costa, A. B.·Vahdat, A.·Kallenborn, F.·Schmidt, B.·Mirdita, M.·Steinegger, M.·Dallago, C.·Chacon, A.

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Abstract

We introduce accelerations for deep learning inference with OpenFold and TensorRT that, combined with MMseqs2-GPU on an x86 system with one NVIDIA RTX PRO 6000 Blackwell Server Edition GPU, reach up to 131x faster inference compared to AlphaFold2. ARM-optimizations enable homology search on power efficient DGX Spark, and allow search beyond available GPU RAM on NVIDIA Grace Hopper Superchip at comparable overall folding speed. These accelerations enable high-throughput protein structure inference at no accuracy cost using familiar tools.

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Didi, K., Sohani, P., Berressem, F., Nesterovskiy, A., Fomitchev, B., Ohannessian, R., Elbalkini, M., Cogan, J., Costa, A. B., Vahdat, A., Kallenborn, F., Schmidt, B., Mirdita, M., Steinegger, M., Dallago, C., Chacon, A.. 2026-03-15. Efficient protein structure prediction fromcompact computers to datacenters withOpenFold-TRT. https://doi.org/10.64898/2026.03.11.711233

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