Generative AI On Mobile Is Running On The Arm CPU


By Adnan Al-Sinan and Gian Marco Iodice 2023 was the year that showcased an impressive number of use cases powered by generative AI. This disruptive form of artificial intelligence (AI) technology is at the heart OpenAI's ChatGPT and Google’s Gemini AI model, with it demonstrating the opportunity to simplify work and advance education through generating text, images, or even audio content ... » read more

SoC Telemetry & Performance Analysis Using Statistical Profiling Extension


The Arm Statistical Profiling Extension (SPE) is an architectural feature designed for enhanced instruction execution profiling within Arm CPUs. This feature has been available since the introduction of the Neoverse N1 CPU platform in 2019, along with performance monitor units (PMUs) generally available in Arm CPUs. An important step in extracting value from capabilities like SPE and PMUs is th... » read more

Flipping Processor Design On Its Head


AI is changing processor design in fundamental ways, combining customized processing elements for specific AI workloads with more traditional processors for other tasks. But the tradeoffs are increasingly confusing, complex, and challenging to manage. For example, workloads can change faster than the time it takes to churn out customized designs. In addition, the AI-specific processes may ex... » read more

CXL’s Protection Mechanisms And How They Handle Real-World Security Problems


A technical paper titled “How Flexible is CXL's Memory Protection?: Replacing a sledgehammer with a scalpel” was published by researchers at University of Cambridge. Abstract: "CXL, a new interconnect standard for cache-coherent memory sharing, is becoming a reality - but its security leaves something to be desired. Decentralized capabilities are flexible and resilient against malicious a... » read more

Transient Execution Attacks That Leaks Arbitrary Kernel Memory (ETH Zurich)


A technical paper titled “Inception: Exposing New Attack Surfaces with Training in Transient Execution” was published by researchers at ETH Zurich. Abstract: "To protect against transient control-flow hijacks, software relies on a secure state of microarchitectural buffers that are involved in branching decisions. To achieve this secure state, hardware and software mitigations restrict or... » read more

Programming Processors In Heterogeneous Architectures


Programming processors is becoming more complicated as more and different types of processing elements are included in the same architecture. While systems architects may revel in the number of options available for improving power, performance, and area, the challenge of programming functionality and making it all work together is turning out to be a major challenge. It involves multiple pr... » read more

64-Bit RISC-V Microprocessor Delivers New Options For IoT Edge Development


Global and rapidly expanding IoT edge devices are becoming increasingly important for connecting various sensors to the cloud via networks. IoT edge devices are progressively integrating 64-bit microprocessors capable of running Linux and similar high-performance operating systems. Moreover, recent import and export regulation changes have produced a need for choices in CPU architecture for mic... » read more

Scaling, Advanced Packaging, Or Both


Chipmakers are facing a growing number of challenges and tradeoffs at the leading edge, where the cost of process shrinks is already exorbitant and rising. While it's theoretically possible to scale digital logic to 10 angstroms (1nm) and below, the likelihood of a planar SoC being developed at that nodes appears increasingly unlikely. This is hardly shocking in an industry that has heard pr... » read more

Effect of Different Frequency Scaling Levels on Memory in Regard to Total Power Consumption in Mobile MPSoC


New technical paper titled "CPU-GPU-Memory DVFS for Power-Efficient MPSoC in Mobile Cyber Physical Systems" from researchers at University of Essex, Nosh Technologies, and University of Southampton. Abstract "Most modern mobile cyber-physical systems such as smartphones come equipped with multi-processor systems-on-chip (MPSoCs) with variant computing capacity both to cater to performance r... » read more

How Inferencing Differs From Training in Machine Learning Applications


Machine learning (ML)-based approaches to system development employ a fundamentally different style of programming than historically used in computer science. This approach uses example data to train a model to enable the machine to learn how to perform a task. ML training is highly iterative with each new piece of training data generating trillions of operations. The iterative nature of the tr... » read more

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