Porting existing CPU applications to NVIDIA GPUs can unlock performance gains, enabling users to solve problems at a much greater scale and speed. While the process of adapting code for NVIDIA GPU acceleration requires an initial investment of time and effort, the resulting improvements in throughput and efficiency often far outweigh the costs. Such an undertaking may seem daunting and raise…
]]>End clients are working on converged HPC quant finance and AI business solutions. Dell Technologies, along with NVIDIA, is uniquely positioned to accelerate generative AI workloads and data analytics as well as high performance computing (HPC) quantitative financial applications where converged HPC quantitative finance plus AI workloads are the need of the hour for clients.
]]>Lowering response times to new market events is a driving force in algorithmic trading. Latency-sensitive trading firms keep up with the ever-increasing pace of financial electronic markets by deploying low-level hardware devices like Field Programmable Gate Arrays (FPGAs) and Application Specific Integrated Circuits (ASICs) into their systems. However, as markets become increasingly…
]]>Hybridizer is a compiler from Altimesh that lets you program GPUs and other accelerators from C# code or .NET Assembly. Using decorated symbols to express parallelism, Hybridizer generates source code or binaries optimized for multicore CPUs and GPUs. In this blog post we illustrate the CUDA target. Figure 1 shows the Hybridizer compilation pipeline. Using parallelization patterns such as…
]]>