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Hardware Optimisations for Crypto High-Frequency Trading and ZKPs Part I
CPUs vs GPUs vs FPGAs
Introduction:
In the dynamic and highly competitive world of high-frequency trading (HFT), especially in the cryptocurrency market, optimizing the performance of trading algorithms is paramount. Field-Programmable Gate Arrays (FPGAs) offer significant advantages for this purpose, particularly in environments where low latency and high throughput are crucial. This article explores the technical specifics of implementing algorithms on FPGAs versus GPUs or CPUs, with a focus on spotting and optimizing FPGA implementations for MEV (Maximal Extractable Value) opportunities in crypto trading.
Technical Considerations for FPGA, GPU, and CPU:
Parallel Processing Capabilities:
- FPGAs: Excellent at handling multiple parallel tasks due to their reconfigurable logic blocks. Ideal for algorithms that benefit from parallel execution, such as those used in MEV strategies where multiple transaction orders need to be processed simultaneously.
- GPUs: Also strong in parallel processing, but generally designed for a higher level of data parallelism suited for graphics rendering or large-scale scientific computations.
- CPUs: Less efficient at parallel processing compared to FPGAs or GPUs. Best suited for sequential task processing.
Latency and Throughput Optimisation:
- FPGAs: Can be finely tuned for low-latency operations, essential in HFT where millisecond differences can impact profitability. FPGAs allow for the implementation of complex trading logic directly into hardware, minimizing the time taken for data processing and decision-making.
- GPUs: While fast, the overhead of managing GPU kernels and memory can introduce latency that might be detrimental in HFT scenarios.
- CPUs: Generally have higher latency and are less efficient in throughput compared to FPGAs and GPUs.
Energy Efficiency:
- FPGAs: Consume significantly less power than GPUs and CPUs when optimized for specific tasks, which is…