Posts by Tharun Adithya Srikrishnan
Automating Performance Bottleneck Identification with the TraceLens Agent
- 30 September 2026
GPUs are valuable resources, and it is imperative to make training and inference workloads on them as efficient as possible. Bottlenecks in these workloads can arise from multiple sources, and mitigations vary depending on the source. For example, a kernel may execute well below its achievable throughput, a collective may remain exposed on the critical path, or the device may sit idle while waiting on host-side dispatch. Identifying these bottlenecks is the first step to improving end-to-end performance.
Streamlining Recommendation Model Training on AMD Instinct™ GPUs
- 02 March 2026
Recommendation model training and inference workloads represent a significant portion of computational requirements across industries including e-commerce, social media and content streaming platforms. Unlike LLMs, recommendation models result in to complex and often imbalanced communication across GPUs, along with a higher load on the CPU-GPU interconnect. The ROCm training docker [1] now includes essential libraries for recommendation model training. This blog demonstrates the functionality and ease of training recommendation models using ROCm, along with suggestions for improved configuration of these workloads. We also highlight the inherent benefits of the large HBM size on AMD Instinct™ GPUs for recommendation workloads.