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@@ -29,7 +29,7 @@ RandomX is a proof of work (PoW) algorithm which was designed to close the gap b
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**AesHash1R** refers to an AES-based fingerprinting function described in chapter 3.4. It's capable of processing more than 10 bytes per clock cycle and produces a 512-bit output.
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-**BlakeGenerator** refers to a custom pseudo-random number generator described in chapter 3.4. It's based on the Blake2b hashing function.
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+**BlakeGenerator** refers to a custom pseudo-random number generator described in chapter 3.5. It's based on the Blake2b hashing function.
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**SuperscalarHash** refers to a custom diffusion function designed to run efficiently on superscalar CPUs (see chapter 7). It transforms a 64-byte input value into a 64-byte output value.
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@@ -269,15 +269,15 @@ finalState0 finalState1 finalState2 finalState3
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The final state is the output of the function.
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-### 3.4 BlakeGenerator
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+### 3.5 BlakeGenerator
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BlakeGenerator is a simple pseudo-random number generator based on the Blake2b hashing function. It has a 64-byte internal state `S`.
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-#### 3.4.1 Initialization
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+#### 3.5.1 Initialization
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The internal state is initialized from a seed value `K` (0-60 bytes long). The seed value is written into the internal state and padded with zeroes. Then the internal state is initialized as `S = Hash512(S)`.
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-#### 3.4.2 Random number generation
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+#### 3.5.2 Random number generation
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The generator can generate 1 byte or 4 bytes at a time by supplying data from its internal state `S`. If there are not enough unused bytes left, the internal state is reinitialized as `S = Hash512(S)`.
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@@ -911,7 +911,7 @@ The finalizer and output calculation steps of Argon2 are omitted. The output is
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### 7.2 SuperscalarHash initialization
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-The key value `K` is used to initialize a BlakeGenerator (see chapter 3.4), which is then used to generate 8 SuperscalarHash instances for Dataset initialization.
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+The key value `K` is used to initialize a BlakeGenerator (see chapter 3.5), which is then used to generate 8 SuperscalarHash instances for Dataset initialization.
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### 7.3 Dataset block generation
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Dataset items are numbered sequentially with `itemNumber` starting from 0. Each 64-byte Dataset item is generated independently using 8 SuperscalarHash functions (generated according to chapter 7.2) and by XORing randomly selected data from the Cache (constructed according to chapter 7.1).
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wepeng