Modern atomistic spin simulations combine long stochastic trajectories, thermodynamic sampling, static optimization and multi-image transition-path workflows, all of which rely on repeated evaluation of spin Hamiltonians and become computationally prohibitive on the large lattices required for three-dimensional magnetic textures. We introduce SpinX, a GPU-native atomistic spin simulation framework built around a unified Hamiltonian interface and multiple user-selectable computational backends. Its core is a crystallographic sublattice decomposition that reformulates translationally invariant spin interactions as multi-channel tensor convolutions, enabling dense, sparse and FFT-based convolution backends, while irregular systems are handled by pair-list evaluation and long-range dipolar fields by reciprocal-space FFT. Implemented in JAX, SpinX supports deterministic and stochastic Landau-Lifshitz-Gilbert dynamics, Monte Carlo sampling, static optimization, dynamical spectroscopy and string and geodesic nudged elastic band transition-path calculations on heterogeneous accelerator platforms. A validated mixed-precision mode combines fp32 field evaluation with fp64 spin-state propagation. We validate SpinX against analytical single-spin dynamics, finite-size thermodynamics of bcc Fe and transverse dynamic structure factors. Performance benchmarks show peak throughput exceeding 10 billion spin-site operations per second on a single accelerator and aggregate single-node workloads of over 1 billion atomic spins. Applying this framework to an exchange-stabilized magnetic hopfion, we uncover two competing annihilation channels on a million-spin atomistic lattice: a previously reported axial-collapse pathway and a distinct lateral-rupture pathway with a different transition morphology and activation barrier.(Due to arXiv's limit, the abstract shown here is a shortened version)