# Discover Exaloop's Game-Changing Performance Benefits

Welcome to Exaloop, the ultimate platform for data science and big data analytics. Exaloop redefines speed and efficiency, delivering unparalleled performance that will transform your data-driven projects.

### Experience Lightning-Fast Computations

### Unlock the Potential of Your Hardware

### Accelerate Machine Learning and Beyond

### Seamless and Supercharged

### Performance for Everyone

### Discover the transformative power of speed with Exaloop. Whether you're a data scientist, analyst, or developer, Exaloop’s performance-driven platform will redefine what's possible in your data-driven endeavors.

# Empower Your Data Journey with Exaloop's Parallelism and Multithreading

### Break Free from Bottlenecks

### Harness the Power of Multiple Cores

### Efficiently Scale with Big Data

### Don’t Waste Your Time Reasoning About Complex Code

### Embrace Parallelism and Multithreading with Exaloop

# Embrace Unprecedented Speed with GPU Acceleration

Welcome to Exaloop’s GPU Acceleration: Unleash the True Power of Your Hardware

### Turbocharge Your Workflows

### Elevate Your AI Projects

### Tackle Large Datasets Head-On

### No CUDA or Low-Level Programming Required

### Transform Your Data Journey with Exaloop

# Unleash the Full Potential of your Data Science Libraries with Exaloop's Turbocharged Implementations

**Welcome to Exaloop’s Optimized Libraries: Your Gateway to Unparalleled Performance**

### A Performance Boost like Never Before

### Synergize with GPU

### Integrate with Parallelism and Multithreading

### Streamlined Performance, No Expertise Required

### Redefine Your Data Science Experience

Speedup over Python

float

pyperformance’s float benchmark — performs a series of 3-dimensional vector operations and normalizations.

Benchmark: nbody

pyperformance’s nbody benchmark — simulates the movement of several celestial objects.

pyperformance’s spectral_norm benchmark — computes the largest singular value of a particular infinite matrix.

Benchmark: primes

Counts prime numbers below a given threshold. Codon version is multi-threaded.

Hans Boehm’s binary-trees benchmark — creates and traverses a number of binary trees.

pyperformance’s fannkuch benchmark — performs, for each permutation of a list, a number of element reversals until a certain condition is met, and computes the maximum number of reversals needed across all permutations. Codon version is multi-threaded.

## Speedup over Python

pyperformance’s float benchmark — performs a series of 3-dimensional vector operations and normalizations.

Benchmark: nbody

pyperformance’s nbody benchmark — simulates the movement of several celestial objects.

pyperformance’s spectral_norm benchmark — computes the largest singular value of a particular infinite matrix.

Benchmark: primes

Counts prime numbers below a given threshold. Codon version is multi-threaded.

Hans Boehm’s binary-trees benchmark — creates and traverses a number of binary trees.

Hans Boehm’s binary-trees benchmark — creates and traverses a number of binary trees.

Hans Boehm’s binary-trees benchmark — creates and traverses a number of binary trees.

Hans Boehm’s binary-trees benchmark — creates and traverses a number of binary trees.

Runtime in seconds

float

pyperformance’s float benchmark — performs a series of 3-dimensional vector operations and normalizations.

pyperformance’s nbody benchmark — simulates the movement of several celestial objects.

pyperformance’s spectral_norm benchmark — computes the largest singular value of a particular infinite matrix.

Counts prime numbers below a given threshold. Codon version is multi-threaded.

Hans Boehm’s binary-trees benchmark — creates and traverses a number of binary trees.

Benchmark: fannkuch

pyperformance’s fannkuch benchmark — performs, for each permutation of a list, a number of element reversals until a certain condition is met, and computes the maximum number of reversals needed across all permutations. Codon version is multi-threaded.

## Runtime in seconds

pyperformance’s nbody benchmark — simulates the movement of several celestial objects.

Counts prime numbers below a given threshold. Codon version is multi-threaded.

Hans Boehm’s binary-trees benchmark — creates and traverses a number of binary trees.

Benchmark: fannkuch

pyperformance’s fannkuch benchmark — performs, for each permutation of a list, a number of element reversals until a certain condition is met, and computes the maximum number of reversals needed across all permutations. Codon version is multi-threaded.