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airhacks.fm podcast with adam bien

airhacks.fm podcast with adam bien

By: Adam Bien
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About this listen

 Java, Serverless, Clouds, Architecture and Web conversations with Adam BienAdam Bien, copyright 2022
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Episodes
  • Accelerating LLMs with TornadoVM: From GPU Kernels to Model Inference

    Accelerating LLMs with TornadoVM: From GPU Kernels to Model Inference
    May 18 2025
    An airhacks.fm conversation with Juan Fumero (@snatverk) about: tornadovm as a Java parallel framework for accelerating data parallelization on GPUs and other hardware, first GPU experiences with ELSA Winner and Voodoo cards, explanation of TornadoVM as a plugin to existing JDKs that uses Graal as a library, TornadoVM's programming model with @parallel and @reduce annotations for parallelizable code, introduction of kernel API for lower-level GPU programming, TornadoVM's ability to dynamically reconfigure and select the best hardware for workloads, implementation of LLM inference acceleration with TornadoVM, challenges in accelerating Llama models on GPUs, introduction of tensor types in TornadoVM to support FP8 and FP16 operations, shared buffer capabilities for GPU memory management, comparison of Java Vector API performance versus GPU acceleration, discussion of model quantization as a potential use case for TornadoVM, exploration of Deep Java Library (DJL) and its ND array implementation, potential standardization of tensor types in Java, integration possibilities with Project Babylon and its Code Reflection capabilities, TornadoVM's execution plans and task graphs for defining accelerated workloads, ability to run on multiple GPUs with different backends simultaneously, potential enterprise applications for LLMs in Java including model distillation for domain-specific models, discussion of Foreign Function & Memory API integration in TornadoVM, performance comparison between different GPU backends like OpenCL and CUDA, collaboration with Intel on Level Zero API and integrated graphics support, future plans for RISC-V support in TornadoVM

    Juan Fumero on twitter: @snatverk
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    1 hr and 11 mins
  • Run Java with Java

    Run Java with Java
    May 11 2025
    An airhacks.fm conversation with Christian Humer (@grashalm_) about: bachelor thesis on a Java bytecode interpreter written in Java, exploration of whether Java could be used as a systems language, benefits of implementing an ecosystem in itself as validation, C1X compiler based on C1 but reimplemented from scratch, concept of sea of nodes for mixing control and data flow, goal to rewrite the entire VM in Java, benefits of using one compiler throughout the stack for compatibility and maintainability, discussion of de-optimization process in JIT compilation, explanation of guards and assumptions in optimized code, three versions of Espresso (Java bytecode interpreter), first version as proof of concept, second version using Truffle with serialized ASTs, third version based on bytecodes with unrolling bytecode loops, explanation of bytecode quickening technique, sandboxing capabilities in GraalVM as replacement for deprecated security manager, isolating untrusted code in separate heaps for security, protection against speculative execution attacks, use case for running AI-generated Java code safely in isolated environments, GraalOS as a minimal operating system for running Java isolates, TRegex as GraalVM's optimized regular expression engine that compiles regex to machine code, bytecode interpreter DSL for generating efficient bytecode interpreters for different languages, memory improvements from using bytecode arrays instead of AST objects, potential future integration of TRegex as a Java API

    Christian Humer on twitter: @grashalm_
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    1 hr and 2 mins
  • LittleHorse Likes Sun

    LittleHorse Likes Sun
    May 4 2025
    An airhacks.fm conversation with Colt McNealy (@coltmcnealy) about: first computing experience with Sun workstations and network computing, background in hockey and other sports, using system76 Linux laptops for development, starting programming in high school with Java and later learning C, fortran, assembly, C++ and python, working at a real estate company with kubernetes and Kafka, the genesis of LittleHorse from experiencing challenges with distributed microservices and workflow management, LittleHorse as an open source workflow orchestration engine using Kafka as a commit log rather than a message queue, building a custom distributed database optimized for workflow orchestration, the recent move to fully open source licensing, comparison with AWS Step Functions but with more capabilities and open source benefits, using RocksDB and Kafka Streams for the underlying implementation, performance metrics of 12-40ms latency between tasks and hundreds of tasks per second, the multi-tenant architecture allowing for serverless offerings, integration with Kafka for event-driven architectures, the distinction between orchestration and choreography in distributed systems, using Java 21 with benefits from virtual threads and generational garbage collection, plans for Java 25 adoption, the naming story behind "Little Horse" and its competition with MuleSoft, the Sun Microsystems legacy and innovation culture, recent adoption of Quarkus for some components, the "Know Your Customer" flow as the Hello World example for Little Horse, the importance of observability and durability in workflow management, plans for serverless offerings and multi-tenant architecture, the balance between open source core and commercial offerings

    Colt McNealy on twitter: @coltmcnealy
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    1 hr and 4 mins

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