HyperTensor-VM
A 2.2M SLOC GPU runtime executing Quantized Tensor Train operations directly on NVIDIA hardware. Custom Triton kernels, cuBLAS GEMM, and cuSOLVER serve all query patterns from compressed form in VRAM.
GPU-native execution on structural form.
Data stays in VRAM as QTT cores. Every operation (search, aggregation, feature serving, streaming) executes on the compressed representation directly. No decompression step.
Kernel components.
Custom Triton Kernels
GPU-optimized QTT operations and structural transformations.
cuBLAS GEMM
Tensor contractions and linear algebra on compressed cores.
cuSOLVER
Decomposition, factorization, and eigenvalue operations.
Memory Management
Custom VRAM allocation and lifecycle management.
Optimized for HBM.
H100 80GB HBM3
Primary validation target for the HyperTensor-VM runtime.
H200 141GB HBM3e
Expanded validation surface for larger workloads.
The VM is optimized for NVIDIA's HBM architecture. Higher memory bandwidth directly translates to lower query latency and larger workload capacity.