❓ About SiPearl…

SiPearl is the European fabless designer of sovereign secure high-performance energy-efficient CPUs for HPC, AI and data centres. These CPUs will help address strategic challenges in the fields of security, defence, medical research, energy, climate and engineering with a reduced environmental footprint.

In June 25, SiPearl completed the design of the most complex CPU ever designed in Europe, Rhea1. Featuring 80 Arm Neoverse V1 cores, with 61 billion transistors, it is currently in production at TSMC. Sipearl CPUs will equip the two first European exascale supercomputers belonging to EuroHPC JU: Rhea1 will be integrated into the JUPITER machine based in Germany and Rhea2 will be part of Alice Recoque in France.

Incubated within the European Processor Initiative (EPI) consortium and seed-funded by the European Union, SiPearl employs almost 200 people in :

• France (Maisons-Laffitte, Grenoble, Massy, Sophia Antipolis),

• Spain (Barcelona)

• and Italy (Bologna)

Following a €130 million Series A, the company has launched its Series B round.

🎯Missions

Modern systems often feature heterogeneous memory (DDR + HBM, NUMA nodes, complex SoC interconnects), making it difficult to understand memory behavior. Traditional tools rarely provide physical address heatmaps, so it’s unclear which memory regions are accessed and how data flows through interconnects.

This internship will explore DAMON (Data Access MONitor), particularly DAMO, to visualize memory access patterns at the physical address level and support the Linux Kernel team in analyzing and optimizing memory usage.

During this internship, you will:

• Study and analyze heterogeneous memory architectures including DDR, HBM, NUMA nodes, and SoC interconnect fabrics (SN-F / HN-F nodes)

• Investigate memory access patterns under specific workloads (e.g., stress-ng) and real-world benchmarks

• Explore and evaluate the use of DAMON (Data Access MONitor), particularly DAMO, to visualize memory accesses at the physical address level

• Develop tools or scripts to collect, process, and visualize memory access data

• Analyze results to better understand memory behavior and performance bottlenecks

• Document your findings, methodology, and tools for the Linux kernel team

🔍What makes you a good match for the role

• Student in the final year of an engineering school or pursuing a Master's degree in electronics, computer engineering, or a related field

• Good understanding of Linux kernel internals

• Strong C and Linux kernel fundamentals (memory management, paging, NUMA, sysfs)

• Good understanding of computer architecture (DDR, HBM, memory controllers, interconnects, cache hierarchy)

• Familiarity with performance analysis tools (e.g., perf, stress-ng, PMU counters)

• Good written and spoken English

📍 Location -> Castelldefels