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v2021.02.0
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@ohadmo ohadmo released this 17 Mar 10:47
· 63 commits to dev since this release
v2021.02.0
c1c5ff8

  • CUDA Mapper

    • Created a new interface to work with Indices. Allow grouping Indices together through public API.
    • Added support for Index from descriptor objects and use that throughout.
    • Added API support for outputting sequences/alignments in SAM/BAM format
    • Determining positions of reads' minimizers on device instead of on host
    • Correctly skipping reads that are too short to fit in at least one window
    • #557 and #562 correct errors in the evaluate_paf script that could result in incorrect counts of matched starts / ends of records or precision and recall values that were greater than 1.

  • CUDA Aligner

    • Fixed a bug in banded Myers which could lead to an out-of-bounds access for non-optimal alignments. If the backtrace in the Needleman-Wunsch matrix touched the border of the band at a specific point it may lead to an out-of-bounds access.
    • Added support for the extended CIGAR format, which distinguishes between matches = and mismatches X.
    • Improved performance for batches with very varying alignment lengths
    • Added a FixedBandAligner base class (as specialization of Aligner) for aligners that operate on a diagonal band. These aligners provide a aligner->reset_bandwidth(new_bandwidth) function now.
    • Fixed the memory requirements of Hirschberg-Myers aligner. It can now process significantly larger batches at once.
    • The default aligners returned by create_aligner() are the banded Myers aligner (a FixedBandAligner) for the create_aligner() function that does specify a bandwidth and Hirschberg-Myers aligner (a Aligner) for the create_aligner() call that does not specify a bandwidth. The API for the latter case is deprecated in will be replaced by a different create_aligner() function.

  • CUDA Partial Order Aligner (CUDA POA)

    • #551 Adds GFA output of the alignment graph generated by cudaPOA.
    • Applied various changes to optimize performance of kernels for banded alignments.
    • Added option -s for CUDA POA API to allow managing allocated memory for adaptive score matrix
    • Introduced static_band_traceback as a new alignment mode in CUDA POA. This mode can potentially improve performance for processing long-read batches.
    • Introduced adaptive_band_traceback for long-read batches. Different banded versions of Needleman-Wunsch kernels were unified.
    • Added new CI tests to validate results of static/adaptive-band and static/adaptive-band with traceback against full-band Needleman-Wunsch kernel.
    • Added description and hints to CUDA POA error codes.
    • Added support for caching device allocations to reduce time spent allocating device memory.

  • CUDA Extender

    • New Added new C++ module for CUDA-accelerated ungapped seed-extension algorithm that uses seed positions in encoded input strands to extend and compute the alignment between the strands, adapted from SegAlign's Ungapped Extender - S. Goenka, Y. Turakhia, B. Paten and M. Horowitz, "SegAlign: A Scalable GPU-Based Whole Genome Aligner," in 2020 SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Atlanta, GA, US, 2020 pp. 540-552.

  • Pygenomeworks

    • CIGAR strings for pairwise alignments can now be visualized.

  • Other

    • System requirements are updated.
    • GenomeWorks semantic versioning is changed to calendar versioning.
    • DevicePreallocatedAllocator allocates exactly the amount of memory requested
    • Fixed silent execution errors, which could occur at GPU kernel launch under certain conditions.
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