Hardware Accelerator RTL Practice Problems

Build the basic signed INT8 multiply-accumulate datapath used in DSP and machine-learning accelerators.

Implement a four-lane signed INT8 dot-product datapath similar to a small neural-network vector unit.

Create a parallel reduction block that sums eight 16-bit lanes into one output.

Implement a hardware activation stage that applies ReLU and saturates positive values to unsigned 8-bit range.

Build a single processing element for a small systolic matrix-multiply array.

Implement a one-cycle-latency signed multiplier with an aligned valid signal, a common accelerator pipeline building block.

Build a combinational population-count unit that returns the number of set bits in a 32-bit word.

Implement a four-lane signed max-reduction datapath.

Multiply two signed Q1.7 fixed-point values and return a truncated Q1.7 result.

Build a streaming accumulator that updates only on successful ready/valid transfers.

Implement a small combinational 2x2 signed matrix-multiply datapath.

Create the arithmetic core of a small 1D convolution engine.

Build the arithmetic primitive used by the FIR datapath.

Compute the combinational weighted sum for four delayed samples.

Reduce a wide accumulator to a 16-bit output without wraparound on overflow.

Create the processing element used repeatedly in the matrix accelerator.

Implement the arithmetic kernel for a 2x2 matrix result element.

Capture two 2x2 input matrices so computation is isolated from the input interface.

Sequence input acceptance, one compute phase and output availability.

Store four result elements until the consumer accepts the complete output tile.

Integrate the complete parallel 2x2 matrix-multiplication datapath with input and output handshakes.

Maintain the current and previous two image rows needed by a 3x3 streaming convolution.

Build the nine-pixel window presented to a 3x3 convolution kernel.

Compute a signed 3x3 dot product between nine pixels and nine kernel coefficients.

Align output validity with a three-stage convolution datapath.

Convert a wide signed convolution result into an unsigned 8-bit pixel using saturation.

Integrate a streaming 3x3 convolution engine with valid/ready flow control.

Implement one 32-bit SIMD lane with add, subtract, minimum and maximum operations.

Apply the same arithmetic operation independently to four 32-bit lanes.

Selectively update SIMD lanes using a four-bit predicate mask.

Reduce four signed lanes to either their sum or maximum.

Integrate four arithmetic lanes with per-lane masking and a registered output.

Integrate control, address progression and transfer counting for a programmable word-copy engine.