This proposal aims to leverage preprocessed information to expedite the verification process significantly, despite the substantial increase in data size per block, which could vary from 10% to 150% of the original size. This approach primarily targets users with high-speed and unlimited internet connections, offering them an opportunity to download larger volumes of data to speed up the syncing process. By doing so, it seeks to improve overall blockchain operation efficiency and performance, providing a customizable interaction experience where users can adjust the balance between data volume and processing speed based on their specific needs and capabilities.

Another area of interest within the blockchain community is the potential use of GPUs for SECP256K1 signature validations, particularly following the introduction of Schnorr signatures through the Taproot upgrade. The discussion around offloading SIGHASH computations to GPUs has been ongoing, as highlighted in forums such as BitcoinTalk and GitHub issues like this one. Despite the theoretical benefits GPUs may offer due to their ability to efficiently handle parallel computations, there has been little progress toward actual implementation. The batch verification of Schnorr signatures, a feature enabled by Taproot, raises further questions about the practicality of utilizing GPUs. Batch verification allows multiple transactions to be validated simultaneously, potentially diminishing the need for GPU assistance. It's important to note that while batch verification improves speed over individual verifications, the performance gains are not linear in relation to the number of signatures checked, with documentation suggesting a speed-up factor of approximately two.

The general consensus suggests that GPUs may not be effective for validating Bitcoin transactions due to the nature of the operations involved, which require random access to cached memory - a task for which GPUs, optimized for vector computations and uniform memory access, are not well-suited. Additionally, many CPUs now include hardware implementations for SHA256 calculations, potentially offering a more efficient solution than GPUs for hashing operations critical to Bitcoin's consensus mechanisms. The complexity and branching required in calculating SIGHASH, depending on its type, make transaction validation processes poorly aligned with GPU strengths. While certain calculations, like SECP256K1 signature validations, could theoretically benefit from GPU capabilities in SIMD vectorized computations, the advent of Schnorr signatures and the possibility of batch validation under Taproot diminishes the potential advantages of GPU usage for these tasks. This assessment underscores the importance of continuous research and adaptation in blockchain technology development, considering the evolving nature of the field and the implementation specifics of platforms like Bitcoin Core.