Fundamental GPU Support

This MR introduces the fundamentals of GPU support to the new backend

General

• Introduce GenericGpu platform and threads range export: GPU platforms communicate the kernel's required thread grid size to the outside via a GpuThreadsRange object separate from the AST
• Add configuration options relating to GPUs

CUDA Platform

• Introduce CUDA platform
• Add materialization + guards for full and sparse iteration spaces
• Add materialization of math functions

SYCL Platform

• Introduce SYCL platform
• Add materialization + guards for full and sparse iteration spaces
• Add materialization of math functions

CUDA Just-In-Time Compiler

• Migrate implementation of cupy-based JIT to new backend as an object-oriented structure

Deviations and Missing Features

In the new implementation, block size selection is entirely up to the JIT / the runtime system and no longer affects the backend. Adaptive block sizes, register restrictions, etc. are not yet implemented by this MR.

src/pystencils/backend/jit/__init__.py

@@ -27,14 +27,9 @@ Both are available here through `LegacyCpuJit` and `LegacyGpuJit`.
 """
 
 from .jit import JitBase, NoJit, LegacyCpuJit, LegacyGpuJit
+from .gpu_cupy import CupyJit
 
 no_jit = NoJit()
 """Disables just-in-time compilation for a kernel."""
 
-__all__ = [
-    "JitBase",
-    "LegacyCpuJit",
-    "NoJit",
-    "no_jit",
-    "LegacyGpuJit",
-]
+__all__ = ["JitBase", "LegacyCpuJit", "NoJit", "no_jit", "LegacyGpuJit", "CupyJit"]