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Published October 4, 2020 | Version v0.10.0
Software Open

spcl/dace: DaCe 0.10

Authors/Creators

  • 1. IBM Research
  • 2. swissbiomechanics AG
  • 3. ETH Zurich
  • 4. ETH Zürich and MeteoSwiss
  • 5. ETH
  • 6. @status-im @numforge
  • 7. Huawei

Description

What's New?
  • Python frontend improvements: More Python features are supported, such as return values, tuples, and numpy broadcasting. @dace.programs can now call other programs or SDFGs.
  • AMD GPU (HIP) Support: AMD GPUs are now fully supported with HIP code generation.
  • Easy-to-use transformation APIs: Apply transformation compositions with one call, enumerate subgraph matches manually, and many more functions now available as part of the dace API. See the new tutorial for examples.
  • Faster code generation: Backends now generate lower-level code that is more compiler-friendly.
  • Instrumentation interface: Setting the instrument property for SDFG nodes and states enables easy-to-use, localized performance reporting with timers, GPU events, and PAPI performance counters.
  • DaCe VSCode plugin: Interactive SDFG viewer and optimizer as part of Visual Studio Code. Download the plugin here.
  • Type inference and connector types: In addition to automatic type inference, connectors on nodes can now be defined with explicit types, giving more fine-grained control over type reinterpreting and vector types.
  • Subgraph transformations: New transformation type that can work on arbitrary subgraphs. For example, fuse any computation within a state with SubgraphFusion.
  • Persistent GPU kernel schedule: Launch persistent kernels with a change of a property! Proportion used of GPU multiprocessors is configurable.
  • More transformations: Loop manipulation and other new transformations now available with DaCe. Some transformations (such as Vectorization) made more robust to corner cases.
  • More tools: Use sdfgcc to quickly compile and optimize .sdfg files from the command line, generating header and library files. Great for interoperability and Makefiles.
  • Short DaCe annotation: Data-centric functions can now be annotated with @dace.
  • Many minor fixes and additions: More library nodes (such as einsum) and new properties added, enabling faster performance and more productive high-performance coding than ever.

Files

spcl/dace-v0.10.0.zip

Files (1.6 MB)

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Additional details

Related works

Is supplement to
https://github.com/spcl/dace/tree/v0.10.0 (URL)