Releases: NVlabs/timeloop
Timeloop v3.0.3 (Ruby)
What's Changed
Several incremental but critical updates:
- Fix bugs in "precise" multicast hop-count estimation.
- Overhaul distributed-multicast modeling approach and make it work with precise hop-count estimation (in prior releases it would only work with probabilistic hop-count estimation).
- Deprecate probabilistic hop-count estimation.
Full Changelog: v3.0.1...v3.0.3
Timeloop v3.0.2 (Ruby)
Add the ability to minimum factors (>=) to mapspace constraints.
Full Changelog: v3.0.1...v3.0.2
Timeloop v3.0.1 (Ruby)
Hotfix release. Fixes bug in outermost-level bypass processing.
Full Changelog: v3.0...v3.0.1
Timeloop v3.0 (Ruby)
Ruby is the third (v3.0) release of Timeloop. The headline feature of this release is support for Imperfect Factorization (described in Horeni et. al., ISPASS 2022), with @MarkHoreni serving as the primary contributor.
Other major changes include support for flattened mappings and spatially-skewed mappings, and countless bugfixes.
v3.0's inputs are backward compatible with those of v2.0.
Full Changelog: v2.0...v3.0
Timeloop v2.0 (Sparseloop)
Sparseloop is the second release (v2.0) of Timeloop. In this release, we added support for modeling sparsity-related hardware optimizations: gating, skipping, and compression. The impact of these optimizations is modeled using statistical characterization of workload densities (fixed structured and hypergeometric).
v2.0’s inputs are backward compatible with those of v1.0.
Full Changelog: v1.0...v2.0
Timeloop v1.0
First stable release. Includes mapper (with linear, random and hybrid search heuristics) and model (with Accelergy integration and support for imperfectly-factorized mappings). Supports modeling of dense (uncompressed) workloads.