Hardware Accelerator
Practice MACs, reductions, fixed-point arithmetic, matrix/conv datapaths and throughput-oriented streaming pipelines.
Practice problems
Use these exercises to build the core implementation and verification skills for this path.
Signed INT8 Multiply-Accumulate
Build the basic signed INT8 multiply-accumulate datapath used in DSP and machine-learning accelerators.Four-Lane INT8 Dot Product
Implement a four-lane signed INT8 dot-product datapath similar to a small neural-network vector unit.Eight-Lane Reduction Adder
Create a parallel reduction block that sums eight 16-bit lanes into one output.ReLU with 8-bit Saturation
Implement a hardware activation stage that applies ReLU and saturates positive values to unsigned 8-bit range.Systolic Array Processing Element
Build a single processing element for a small systolic matrix-multiply array.Valid-Tagged Pipelined Multiplier
Implement a one-cycle-latency signed multiplier with an aligned valid signal, a common accelerator pipeline building block.32-bit Population Count
Build a combinational population-count unit that returns the number of set bits in a 32-bit word.Four-Lane Signed Vector Maximum
Implement a four-lane signed max-reduction datapath.Q1.7 Fixed-Point Multiplier
Multiply two signed Q1.7 fixed-point values and return a truncated Q1.7 result.Valid-Ready Streaming Accumulator
Build a streaming accumulator that updates only on successful ready/valid transfers.2x2 Matrix Multiply Datapath
Implement a small combinational 2x2 signed matrix-multiply datapath.Three-Tap INT8 Convolution
Create the arithmetic core of a small 1D convolution engine.
Build the basic signed INT8 multiply-accumulate datapath used in DSP and machine-learning accelerators.Four-Lane INT8 Dot Product
Implement a four-lane signed INT8 dot-product datapath similar to a small neural-network vector unit.Eight-Lane Reduction Adder
Create a parallel reduction block that sums eight 16-bit lanes into one output.ReLU with 8-bit Saturation
Implement a hardware activation stage that applies ReLU and saturates positive values to unsigned 8-bit range.Systolic Array Processing Element
Build a single processing element for a small systolic matrix-multiply array.Valid-Tagged Pipelined Multiplier
Implement a one-cycle-latency signed multiplier with an aligned valid signal, a common accelerator pipeline building block.32-bit Population Count
Build a combinational population-count unit that returns the number of set bits in a 32-bit word.Four-Lane Signed Vector Maximum
Implement a four-lane signed max-reduction datapath.Q1.7 Fixed-Point Multiplier
Multiply two signed Q1.7 fixed-point values and return a truncated Q1.7 result.Valid-Ready Streaming Accumulator
Build a streaming accumulator that updates only on successful ready/valid transfers.2x2 Matrix Multiply Datapath
Implement a small combinational 2x2 signed matrix-multiply datapath.Three-Tap INT8 Convolution
Create the arithmetic core of a small 1D convolution engine.
Projects for this path
Use the projects to combine individual skills into larger portfolio-ready systems.
Matrix-Multiplication Accelerator
Build a small parallel matrix engine from processing elements and tile registers through control, buffering and top-level handshakes.Convolution Accelerator
Build a streaming 3x3 convolution datapath with row buffering, sliding windows, parallel MAC arithmetic, valid alignment and saturated output.DMA Engine
Build the data-movement engine accelerators need: programmable registers, source/destination sequencing, backpressure, transfer counting and completion interrupts.Hardware DSP Pipeline
Build a streaming FIR-style datapath with signed MAC arithmetic, sample history, control alignment and saturation.FPGA Packet Parser
Build a fixed-latency Ethernet/IPv4/UDP parser with field extraction and line-rate statistics without full-frame buffering.Timestamped Feed-to-Action Pipeline
Makes latency engineering measurable and gives you a strong artifact to discuss in FPGA/HFT interviews.
Open the interactive Hardware Accelerator roadmapBuild a small parallel matrix engine from processing elements and tile registers through control, buffering and top-level handshakes.Convolution Accelerator
Build a streaming 3x3 convolution datapath with row buffering, sliding windows, parallel MAC arithmetic, valid alignment and saturated output.DMA Engine
Build the data-movement engine accelerators need: programmable registers, source/destination sequencing, backpressure, transfer counting and completion interrupts.Hardware DSP Pipeline
Build a streaming FIR-style datapath with signed MAC arithmetic, sample history, control alignment and saturation.FPGA Packet Parser
Build a fixed-latency Ethernet/IPv4/UDP parser with field extraction and line-rate statistics without full-frame buffering.Timestamped Feed-to-Action Pipeline
Makes latency engineering measurable and gives you a strong artifact to discuss in FPGA/HFT interviews.