Upgrade Dr.Jit to version 1.1.0. The following list summarizes major new features added to Dr.Jit. See the Dr.Jit release notes for additional detail and various smaller features that are not listed here. Cooperative vectors and a neural network library: Dr.Jit now supports efficient matrix-vector arithmetic that compiles to tensor core machine instructions on NVIDIA GPUs. A modular neural network library facilitates evaluating and optimizing fully fused MLPs in rendering code. (Dr.Jit PR #384, Dr.Jit-Core PR #141). Hash grid encoding: Neural network hash grid encoding inspired by Instant NGP, including both traditional hash grids and permutohedral encodings for high-dimensional inputs. (Dr.Jit PR #390, contributed by Christian Döring and Merlin Nimier-David). Function freezing: The @drjit.freeze decorator eliminates repeated tracing overhead by caching and replaying JIT-compiled kernels, which can dramatically accelerate programs with repeated computations. (Dr.Jit PR #336, Dr.Jit-Core PR #107, contributed by Christian Döring). Shader Execution Reordering (SER): drjit.reorder_threads shuffles threads to reduce warp-level divergence, improving performance for branching code. (Dr.Jit PR #395, Dr.Jit-Core PR #145). New random number generation API: The function drjit.rng returns a drjit.random.Generator object (resembling analogous API in NumPy, PyTorch, etc.) that computes high-quality random variates that are statistically independent within and across parallel streams. (Dr.Jit PR #417). Array resampling and convolution: New functions drjit.resample and drjit.convolve support differentiable signal processing with various reconstruction filters. (Dr.Jit PRs #358, #378). Gradient-based optimizers: New drjit.opt module with drjit.opt.SGD, drjit.opt.Adam, and drjit.opt.RMSProp optimizers. They improve upon the previous Mitsuba versions and include support for adaptive mixed-precision training. (Dr.Jit PRs #345, #402). TensorFlow interoperability: @drjit.wrap enables seamless integration with TensorFlow. (Dr.Jit PR #301, contributed by Jakob Hoydis). Enhanced tensor operations: New functions drjit.concat, drjit.take, drjit.take_interp, and drjit.moveaxis for tensor manipulation. Performance improvements: Packet scatter-add operations, optimized texture access, and faster drjit.rsqrt on the LLVM backend (Dr.Jit PRs #343, #329, #406, Dr.Jit-Core PR #151), The remainder lists Mitsuba-specific additions. Function freezing. Using the previously mentioned @dr.freeze feature, it is now possible to freeze functions that call mi.render(). Rendering another view (e.g., from a different viewpoint or with a different material parameter) then merely launches the previously compiled kernels instead of tracing the rendering process again. This unlocks significant acceleration when repeatedly rendering complex scenes from Python (e.g., in optimization loops or real-time applications). Some related changes in Mitsuba were required to make this possible. (PRs #1477, #1602, #1642, contributed by Christian Döring). AD integrators and moving geometry. All automatic differentiation integrators have been updated to correctly handle continuous derivative terms arising from moving geometry. In particular, the continuous (i.e., non-boundary) derivative of various integrators was missing partial derivative terms that could be required in certain geometry optimization applications. The updated integrators also run ~30% faster thanks to Shader Execution Reordering (SER). (PR #1680). We thank Markus Worchel, Ugo Pavo Finnendahl, and Marc Alexa for bringing this issue to our attention. Gaussian splatting. Two new shape plugins support volumetric rendering applications based on 3D Gaussian splatting: ellipsoids is an anisotropic ellipsoid primitives using closed-form ray intersection, while ellipsoidsmesh uses a mesh-based representation. The volprim_rf_basic integrator renders emissive volumes based on them (PR #1464, contributed by Sebastien Speierer). The new sunsky plugin implements Hosek-Wilkie models for the sun and sky, where sampling of the latter is based on Nick Vitsas and Konstantinos Vardis' Truncated Gaussian Mixture Model. (PR #1473, #1461, #1491, contributed by Mattéo Santini). Shader Execution Reordering (SER). The Scene.ray_intersect() and Scene.ray_intersect_preliminary() methods now accept a reorder parameter to trigger thread reordering on CUDA backends, which shuffles threads into coherent warps based on shape IDs. Performance improvements vary by scene complexity (ranging from 0.67x to 1.95x speedup). SER can be controlled globally via the scene's allow_thread_reordering parameter or by disabling drjit.JitFlag.ShaderExecutionReordering. Most integrators have been updated to use SER by default. (PR #1623). The performance of ray tracing kernels run through the CUDA/OptiX backend was significantly improved. Previously, several design decisions kept Mitsuba off the OptiX "fast path", which is now fixed. (PRs #1561, #1563, #1568). Mitsuba now targets the OptiX 8.0 ABI available on NVIDIA driver version 535 or newer. (PR #1480). Bitmap textures now use half precision by default. (PR #1478.) Improvements to the mitsuba.Shape interface. (PRs #1484, #1485). The Mitsuba optimizers (e.g. Adam) were removed. They are now aliases to more sophisticated implementations in Dr.Jit. (Mitsuba PR #1569, Dr.Jit PR #345). The Transform API became more relaxed—for example, Transform4f.scale() and Transform4f().scale() are now both equivalent ways of creating a transformation. This removes an API break introduced in Mitsuba version 3.6.0. (PR #1638). Refactoring. The codebase underwent several major refactoring passes to remove technical debt: Removal of the legacy thread system and replacement with standard C++ constructs (PR #1622). Removal of the legacy object system and replacement with standard C++ constructs; rewrite of the mi.Properties and plugin loader implementations (PR #1630). Switched to a new parser and scene IR common to both XML and dictionary parsing; further work on mi.Properties (PRs #1669, #1676) Replaced Transform4f by specialized affine and perspective transformations. (PR #1679). Pass over the test suite to accelerate CI test runs (PR #1659) This is part of an ongoing effort to modernize and improve legacy Mitsuba code. Added an API to easily read/write tensor files from Python and access them as Dr.Jit tensor instances in Python/C++ code (PR #1705). The rawconstant texture plugin stores raw 1D/3D values without any color space conversion or spectral upsampling, useful when exact numerical values need to be preserved. (PR #1496, contributed by Merlin Nimier-David). Various minor improvements and fixes. (PRs #1350, #1495, #1496, #1527, #1540, #1545, #1547, #1528, #1583, #1522, #1600, #1627, #1628, #1656, #1663, #1668, #1678, #1696, and #1702).