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A naive implementation of these algorithms is prohibitively slow.
As a result, distance computations are time consuming in a naive implementation of -means.
With algorithm-specific optimizations, the throughput of the system increased threefold from an initial naive implementation.
It turns out that a naive implementation of BRDF representation in terms of spherical harmonics has several problems.
Through experimentations, we show that the naive implementation can reveal some important information about the secret key.
The area of design optimization is where the performance of a design can be made drastically better than an initial naive implementation.
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By clustering nodes directly on the time lines of messages, we propose two naive implementations of CENI: Infection-centric CENI and Cascade-centric CENI.
Aware of the efficiency and consistency issues that affect naive implementations of the view-based approach (cfr. Sect. 3) and aligned with [17] principles, we believe that an effective enforcement approach should combine view generation and query rewriting, taking maximum benefit from the two mechanisms.
Using vectorization, CPU and GPU memory consumption could be substantially reduced compared to the naive reference implementation, in some cases even by an order of complexity.
We highlight our last CR approach which completely avoids updating conflicts of histogram calculation, leading to substantial performance improvements (up to 55× speedup over naive CPU implementation).
The vectorization allowed usage of optimized parallel libraries during forward and reverse passes which resulted in high speedups for the vectorized CPU version compared to the naive reference implementation.
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