Scala Goes Native
Explore Scala Native: a new ahead-of-time compiler and lightweight runtime for Scala, expanding its horizons beyond JVM and enabling native development with improved performance.
Fast Startup and Low Latency - Pick Two
Explore Scala Native for lightweight system programming, enabling fast startup and low latency without JVM complexities. Learn about its features, garbage collection, and performance benchmarks.
Problem Solving Recipes Learned from Supporting Spark
Insights into common Spark pitfalls and how to avoid them. Learn tips and tricks for debugging and optimizing Spark applications, from memory errors to configuration issues and performance optimization.
Lessons to Scala Native from Kotlin Native
Explore insights from Kotlin Native for Scala Native development, covering compilation, memory management, debugging, and practical applications in native environments.
Twitter's Quest for a Wholly Graal Runtime
Explore Twitter's journey to optimize runtime performance using GraalVM, addressing compilation issues, memory leaks, and cost-efficiency in large-scale server deployments.
Fast, Simple Concurrency with Scala Native
Explore fast, simple concurrency in Scala Native using libuv. Learn about event loops, streams, and performance optimization for systems programming and network applications.
Compiling to Preserve Our Privacy
Explore secure multiparty computation and privacy-preserving techniques in Scala, including direct embedding, masking, and compiler optimizations for efficient implementation.
Slinc - A Library for Scala to C Interoperability
Explore Slinc, a Scala 3 library enabling seamless C interoperability. Learn how it leverages advanced features to simplify C bindings, enhancing Scala's capabilities for high-performance computing and machine learning.
Building Billion Node Graphs for Machine Learning
Explore building billion-node graphs for machine learning, covering data ingestion, graph management, and algorithm execution at scale. Learn about challenges and solutions in handling massive datasets for GraphML research.
Automatic GC Compaction in MRI
Explore automatic GC compaction in Ruby 2.7, its implementation challenges, and techniques like read barriers and concurrent GC. Learn about memory optimization and performance improvements in Ruby applications.
The Bug that Forced Me to Understand Memory Compaction
Explore Ruby's memory management, from heap allocation to garbage collection and memory compaction, through a bug-solving journey in a gem maintenance story.
Railsbench - Rdoc Generation - Microbenchmarks - Proposal to Enable VWare Resizing Objects - Shrinking RVALUE
Explore Ruby's memory optimization project to improve performance by moving system heap memory into Ruby heap memory, reducing allocations and enhancing CPU cache efficiency.
Scaling Rails with JRuby in 2022
Explore JRuby's benefits for scaling Rails applications, including improved performance, resource efficiency, and true parallel threading on the Java Virtual Machine.
Using JRuby - What, When, How, and Why
Explore JRuby: its compatibility, benefits, and real-world applications. Learn about JVM advantages, installation, Rails integration, and performance benchmarks for informed Ruby development decisions.
Uptime - Building Resilient Services with Go
Explore resilient Go service development, focusing on concurrency, error handling, memory management, and monitoring techniques for improved performance and reliability.
Understanding Channels
Explore the inner workings of Go channels, their operations, and how they interact with runtime systems for effective goroutine communication and concurrency patterns.
The Scheduler Saga
Explore the inner workings of Go's scheduler, including goroutine management, network IO coordination, and memory management mechanisms for efficient program execution.
Controlling the Go Runtime
Explore techniques to control the Go runtime, including garbage collection, goroutine management, and affinity. Learn new methods for better runtime control and their practical applications.
Two Go Programs, Three Different Profiling Techniques
Explore three profiling techniques for Go programs to diagnose and improve performance, including CPU and memory profiling, execution tracing, and understanding Amdahl's Law.
Pardon the Interruption - Loop Preemption in Go 1.14
Explore Go 1.14's innovative asynchronous preemption, eliminating performance issues in tight loops and enabling efficient goroutine scheduling without overhead.
Evolving the Go Memory Manager's RAM and CPU Efficiency
Explore Go memory manager improvements, enhancing runtime responsiveness and allocator scalability. Gain insights into runtime functionality and potential performance impacts on Go applications.