DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In

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Published: 2026-09-01T05:15:55.048Z • Permanent link

Google's highly anticipated launch of its Processing-In-Memory (PIM) technology, codenamed DCC, marks a significant milestone in the evolution of machine learning processing. Led by renowned experts in the field, Dr. Nathan Soska and Dr. Andrew Waterman, Google's research team has been working tirelessly to develop a data-centric compilation of machine learning kernels designed to accelerate memory-intensive kernels of Machine Learning (ML) models. DCC's innovative architecture is set to revolutionize the way ML models are processed, significantly enhancing the processing power of host processors and paving the way for widespread adoption in various industries.

DCC's development is a culmination of years of research and collaboration between Google's engineers and academia. Building on the success of Google's Tensor Processing Units (TPUs), DCC takes the next step by integrating Processing-In-Memory (PIM) devices directly into host processors. This integrated design enables high-performance computing, reducing latency and increasing efficiency. According to a report by Bloomberg, Google's PIM technology has the potential to significantly reduce the latency associated with ML processing, a critical factor in industries such as healthcare, finance, and autonomous vehicles.

Google's announcement of DCC is timely, given the growing demand for ML processing in various sectors. Companies like NVIDIA and Intel are already investing heavily in PIM technology, and the widespread adoption of DCC is expected to have far-reaching implications for the broader technology sector. Dr. Nathan Soska, Google's lead researcher on PIM technology, stated, "We're excited to bring DCC to market, as it has the potential to significantly accelerate ML processing and enable new applications in areas such as natural language processing, computer vision, and predictive analytics.

DCC's impact on the Data Sources domain will be felt across various industries and markets. For companies like NVIDIA and Intel, DCC represents a significant opportunity to expand their offerings and gain a competitive edge in the ML processing market. NVIDIA, in particular, has been investing heavily in PIM technology, and the integration of DCC into their products is expected to further accelerate their growth. Research communities, too, will benefit from DCC's accelerated processing capabilities, enabling the development of more complex and sophisticated ML models.

The adoption of DCC is also expected to have significant implications for the broader technology sector. As DCC becomes more widespread, it is likely to drive innovation and investment in the ML processing space. According to a report by MarketsandMarkets, the global ML processing market is expected to grow from $4.6 billion in 2022 to $14.3 billion by 2027. DCC's integration into host processors is expected to significantly accelerate this growth, creating new opportunities for companies and research institutions alike.

DCC's development is part of a larger trend in the evolution of ML processing. Prior to the development of TPUs, ML processing relied heavily on Graphics Processing Units (GPUs). However, the limitations of GPU-based ML processing became apparent as the complexity and size of ML models increased. The development of TPUs marked a significant shift towards more specialized and efficient ML processing architectures. Now, with the introduction of DCC, we are witnessing a further evolution of ML processing, one that integrates the benefits of both TPUs and PIM devices.

The European Union's efforts to promote the adoption of PIM technology are also worth noting. The EU's Digital Single Market strategy aims to create a unified digital infrastructure across the continent, with a focus on promoting innovation and investment in the ML processing space. The European Digital Service Act 2.0, led by EU Commissioner for Internal Market Thierry Breton, represents a significant step towards creating a more cohesive and competitive digital landscape.