In CUDA parlance, a “block” isn’t made of full CPU-style processors but of threads. You can launch up to 1,024 threads per block (for modern GPUs with compute capability ≥2.0), organized into warps of 32 threads that execute in lockstep on the GPU’s streaming multiprocessors (SMs). The actual number of CUDA cores varies by GPU model—an A100 has 6,912 cores distributed across its SMs—so your block’s threads are dynamically scheduled onto those cores. When you choose an AceCloud GPU instance, you get to pick from NVIDIA’s latest GPUs (A100, H100, RTX A6000), each with its own SM and core counts, so you can tailor block and grid dimensions to maximize occupancy and throughput for your parallel workloads.